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    Evaluating Recruiting Metrics: “Time to Fill” vs. “Speed to Hire”

    Are you tracking time to fill or speed to hire? Well, you should be tracking both. Together they provide insights into different aspects of hiring – from the broader view of the recruitment lifecycle to the specifics of candidate engagement. Tracking these metrics is key to developing an efficient and candidate-friendly hiring process.

    Hired’s Senior Internal Recruiter Jules Grondin says, “Determining which metric to look at more closely depends on what matters most to the company at that moment. 

    Do you want to look at time to fill to determine the cost per req for recruiter hours? 

    Do you want to know the efficiency of their processes when the right candidate does entire the pipeline? 

    Are recruiters interviewing the right talent? Are market trends affecting the pipeline?”

    In this blog, we differentiate speed to hire and time to fill, why both are essential to a strategic hiring process, and when one might be more relevant than the other. 

    What does speed to hire mean?

    At Hired, we define speed to hire as the total time the candidate spends in the hiring funnel from initial sourcing to offer acceptance. It’s the average time it takes you to hire an individual candidate. Viewing the candidate lifecycle in terms of this window is important primarily because it’s the part of the hiring process where the recruitment team can have the most impact.

    Speed is key because it:

    Considers how quickly candidates are actioned and scheduled for interviews

    Proves delivery of great fit candidates who are bullish about the organization

    Illustrates a streamlined offer letter composition and negotiation process

    Lowers the likelihood of losing top talent to competitive offers

    Speed to hire matters to candidates too

    Jules adds, “Candidates like speedy processes. It shows a company’s process is tightly kept and they are in full alignment for what they want in a hire. It’s a good statistic to share with active candidates because they will likely be more eager to engage in your process.”

    The metric as a measure of success: 

    During Hired’s webinar, Raise the Bar in 2023: Strategies from Top Employers Winning Tech Talent, Reece Batchelor, R&D Talent Manager at weighed in on hiring metrics. He says:  

    “It depends on what your company’s goals are. You need to find the right balance. When you only track [speed to hire], it could push you toward neglecting other metrics. We track time to hire because as a recruiter you want to fill a role as quickly as possible. But it’s not the most simple metric. We would rather hire someone exceptional in three months than someone okay in one month. That’s what we really value. 

    I think a better metric to track when you’re trying to determine how efficient the process is the time spent in each stage of the interview process. That drives us to book people in quickly, gain feedback, and give feedback as quickly as possible. If you prioritize something like that to ensure your process is efficient, you understand what great looks like for your hiring managers. Then, you give an excellent candidate experience and time to hire comes naturally.”

    How to optimize speed to hire recruiting metrics

    On board with speed to hire, right? Swell! Time to optimize this puppy. Toward the end of the hiring cycle, as candidates start to look better and better, there’s an opportunity to compress steps together in the interest of saving time.

    For example, start conducting reference calls as soon as a candidate makes it to the final round of interviews. Scheduling and completing these calls sometimes drags, so getting a head start often shaves a few days off your total speed to hire. For extra credit, use these conversations to uncover material for your interviewing team to follow up on as they make their final assessment.

    To further cut down on speed to hire, set reasonable timelines for offer evaluation. Ask your candidate how long they think they’ll need to make a decision.

    What is an exploding offer? 

    An exploding offer is one with an expiration date, typically short, within a few hours or days. It’s designed to force a quick decision, without the opportunity to compare options, procure counsel, or engage in negotiation.

    Avoid having offers floating in limbo and perhaps agree on three to five days maximum. Be proactive when talking about offer evaluation: ask the candidate what they need to consider before making a final decision. This allows you to tweak the offer if necessary, and in some cases, may help them realize they’ve already made their choice.

    Related: 3 Ways You Should Use C-Suite to Recruit Tech Talent (+ Free Templates) 

    What does time to fill mean?

    Time to fill measures the total time between an opened and closed req. It’s vital to gauge the effectiveness and efficiency of the recruitment process. While time to fill gives a broad overview of the hiring cycle, speed to hire offers a more focused insight into the candidate engagement phase.

    Time to fill is key because it:

    Helps organizations understand how quickly they can fill positions and adapt their recruitment strategies accordingly

    Supports in planning and forecasting future hiring needs and timelines

    Improves candidate experience (as a prolonged hiring process might deter top candidates)

    Allows organizations to benchmark their hiring efficiency against industry standards or past performance

    When to use time to fill vs. speed to hire

    It’s important to keep your finger on the pulse of time to fill as it can provide some organizational insights. For example, total headcount projections will be important to your finance team. Further, time to fill is a good measure of how strategic your team is about opening new requisitions. Roles should be opened in the interest of being closed, and if reqs go unfilled for a lengthy amount of time, there is most likely a misalignment of priorities.

    Even in these cases, time to fill isn’t as simple as the average number of days from job open to job close. Break it down both by department and level of seniority, as the variation here can be so vast that a single high-level metric isn’t illustrative of an organizational hiring rate.

    When this metric is applied to clusters of employees more likely to have reliable times to fill, it provides a more accurate projection of when executives can expect desks to be filled.

    As far as calculation goes, you may have to roll up your sleeves to get granular. Find the relevant dates in your ATS, plug them into an easy calendar tool like this one, and you’re all set.

    Jules explains, “Time to fill is an effective metric to see how well recruiters are performing, if they’re recruiting the right talent, and how the market may be affecting this statistic. 

    The longer a role is open, the more a company may need to dig into:

    Which recruiter is running the search

    If you’re recruiting candidates who don’t align with the role

    How your compensation resonates and compares to market rates

    How many inbound applicants you’re getting from the first opening to engagement from the recruiter to process/offer”

    Balancing time to fill and speed to hire

    Both time to fill and speed to hire are crucial for a successful recruitment strategy. The key is to find a balance. A rapid hiring process is desirable, but not at the expense of hiring quality. By tracking and optimizing these metrics, you’ll speed up the hiring process and improve the quality of hires. 

    Originally written by Matt Hughes in July 2017. Updated by the Hired Content Team November 2023. More

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    Difficulty Keeping Your Top Tech Talent? This Could Be Why (& What to Do About It)

    Do You Employ the 65% of Tech Workers Who Plan to Look for a New Job in 2024?
    Are you concerned about tech employee turnover and retention? You’re not alone. If you’re concerned with keeping your top tech talent and employee tenure, you’re in the majority. Hired recently surveyed more than 250 engineering hiring managers, recruiters, talent acquisition professionals, and tech executives and found retention was one of their top three concerns in the next 12 months. In fact, 63% said the cost of vacancy was a key concern for them.
    So, how do you make employee satisfaction a part of your employer branding? How do you lay the foundation for a strong employee tenure early, whether you’re responsible for staffing a startup or enterprise hiring?
    We’ve got you covered in our eBook, Difficulty Keeping Your Top Tech Talent? This Could Be Why (& What to Do About It).
    In it, we’ll explore:

    The real pain points behind the tech industry’s retention challenges. Why traditional interviewing might be the Achilles’ heel of tech hiring.
    The transformative power of reverse interviews in ensuring job role satisfaction and longevity.
    Practical insights on executing reverse interviews effectively and addressing the retention conundrum head-on. More

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    Restart Recruitment Guide: How To Reboot Tech Hiring Post-Freeze

    Have you paused tech recruiting? Persevered through a hiring freeze or slowdown? When it’s time to restart recruitment, where should you start? Keep reading to kickstart your tech hiring after challenging economic times with this guide.
    1. Before you restart recruitment, reassess the current circumstances
    Start by re-evaluating hiring needs. Review the roles that were initially put on hold. Are they still relevant or have your business needs shifted? You’ll also need to understand the new market conditions for a better idea of the employment landscape. 
    Which industries have bounced back and which are still lagging? Are you in a candidate-driven market? How have candidate priorities and expectations changed? 
    Resources like Hired’s 2023 State of Tech Salaries offer detailed insights to adapt and keep moving forward in the current hiring market.
    Related: Less Competition, More Talent: Here’s How to Recruit in an Economic Downturn 
    2. Re-engage with past candidates
    Take inventory of the connections you might already have. Check the availability of past candidates and get back in touch with those who were in the interview process before the freeze. Hopefully, you maintained a feedback loop and shared feedback from previous interviews with candidates. This is an effective way to foster goodwill even if you didn’t hire them.
    3. Review your employer brand and employer value props, or EVPs
    After shaky economic times, people – understandably – may become more cautious when it comes to employers and their stability. Post-downturn, rebuilding trust in your company’s stability and growth is a priority. Be transparent and highlight recovery plans and growth potential in your employer branding.
    It’s also a great time to showcase company culture. This is especially true if your organization’s culture includes supportive elements like mental health initiatives, flexible working options, and employee development programs. 
    Related: 2023 Survey Results: Top 3 Benefits Ranked by Engineers (Besides Salary) 
    4. Invest in training and development
    Sometimes the best hires are internal. Consider investing in training programs to upskill existing employees for new roles, promoting internal mobility. Not to mention, supporting internal mobility and upskilling are great ways to retain talent, support internal candidates, inspire loyalty, and provide professional growth.
    Related: How to Support Internal Candidates When They Don’t Get the Job 
    Offering continuous learning and development opportunities will also attract jobseekers looking for long-term career growth. Our 2023 State of Software Engineers report revealed development and career growth as top priorities for an ideal company culture and work environment according to surveyed engineers.
    Related: How to Nurture Innovation, Strengthen Retention (Use Professional Development) 
    5. Revise your recruitment strategy
    Think back to when you re-evaluated hiring needs. What shifts can you make to your recruitment strategy given the new circumstances? From revising your candidate messaging to rethinking how you conduct interviews, we have a suite of resources to help employers make these updates a little less overwhelming:  

    6. Re-evaluate your recruitment tech stack
    Now is also the time to consider new platforms or tools to support your hiring revamp. Hired, for example, connects employers to a curated pool of experienced and responsive tech talent seeking their next role. The platform also integrates with applicant tracking systems to fully streamline your hiring process. 
    Related: How to Secure Approval for New Tech Tools (Free Template) 

    Restart recruitment lessons learned from Laura MacKinnon, VP of People at Clari
    On Hired’s podcast, Talk Talent to Me, Laura shared learnings from a massive hiring freeze. She gave a few tips on what she would do differently when ready to restart recruitment:  
    “One of the things we did up front was make sure not to bring our recruiting team down to a skeleton crew. We knew these things usually do have a bit of an up-and-down cycle. If we were to have brought our recruiting team down to the need we had at the moment, we would not have enough people respond to the demand. Luckily, we kept our scheduling, sourcing, and recruiting teams around with the hopes the downturn would be short. Being a cloud-based company, we accelerated back to needing to hire engineers along with other people to help lead the business forward. 
    As you can imagine, the head of people is involved with finance, the head of engineering, and the CEO requesting the board to fund additional resources. What I would do with 20/20 hindsight is make sure we also included asking for the increased spending needed to spin up that machine because it was idle. That means not just the recruiters, but money in place for proactive talent sourcing and time with the marketing team to help get the word out that the company is recruiting.”  
    Laura’s tips: 

    Don’t bring the recruiting team down to a skeleton crew
    Get on board when you hear about other teams requesting funds

    Related: Need help talent sourcing? Hired’s got you covered with temporary or ongoing help. 

    6. Secure funding before you restart recruitment
    Laura MacKinnon emphasizes the importance of collaborating with other teams to ensure the recruiting team has a seat at the table. 
    She says, “If you notice a team talking about potentially adding headcount, that’s the time for your Head of Talent to jump in. They should ask to include two recruiters, a sourcer, and a scheduler. The earlier you hear that coming up, the faster you want to jump in so you have funding. If your company is proactive, you can even onboard those people before the official big ask gets approved.”
    Partnership with finance is especially critical because a lot of what recruiting does has a cost. Laura illustrates this with example from Clari: “Diversity and inclusion are such an important part of how we’re going to grow as a business. As opposed to waiting until we’re a thousand people, the needle-moving time is when the company is at its smallest. 
    We want to have a diverse team of men, women, people of color, and any underrepresented groups. Starting with that helps build because a lot of our hiring – probably one-third – will probably come from referrals. Those initial efforts to spin up the machine and make our commitment to that community clear come with a need to fund. It could be through innovative internships for students or being present at events to show Clari wants to be an employer of choice for a diverse population. 
    You need financial support. The more HR can learn how to make business cases that make finance people happy and understand, the better we are at getting funding.”
    Restart Tech Recruitment Checklist:

    Reevaluate hiring needs
    Engage with past candidates
    Update online employer profiles
    Revise recruitment strategy
    Review salary benchmarks
    Plan for onboarding
    Measure effectiveness regularly

    Navigate the upturn
    Emerging from an economic downturn to restart recruitment and hiring can feel daunting. However, with a strategic recalibration and a systematic approach, it’ll be a smooth transition. 
    Restart recruitment for tech and sales roles with Hired! Get a free demo. More

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    Dear Developers: Coding Languages That Will Set You Apart in 2023

    Any software engineer will tell you: There are a plethora of coding languages out there and varying attitudes toward each at both the company and individual levels. To dive deeper, Hired’s 2023 State of Software Engineers report examines coding languages that set candidates apart from their peers and the preferences of developers.

    Which programming skills were highest in demand by employers? 

    In 2022, engineers skilled in Ruby on Rails received 1.64X more interview requests compared to Hired’s marketplace average. This year, Ruby on Rails moved up one position to take the top slot as the most in-demand engineer skill. Ruby and Scala came in second and third.

    Hired CTO Dave Walters said, “Ruby on Rails is a very mature and easy-to-use framework, which leads to its popularity among engineers and engineering leaders. It allows for faster coding (or increased productivity) which helps engineers deliver minimum viable products and features at a higher pace.”

    In 2021, the leading programming skill was Go. Larger companies such as Slack and Twitch rapidly adopted it last year. Its simplicity and power made it popular among engineers. Dave added, “While a favorite among engineers, Go may be less in demand by employers now due to a temporary shift in hiring needs.”

    Related: Inside the Coding Challenge: A Hiring Manager’s Perspective 

    How the engineers feel about coding skills

    Employer demands aside, developers themselves have their own opinions of the different coding languages. This is often due to how many resources there are for learning and development related to a particular language or how “fun” they are to use.

    In our survey of over 1,300 software engineers, we found engineers ranked Python as their favorite programming language. JavaScript and Java followed as the second and third choices.

    Beyond coding languages

    Knowing which languages will set you apart from the rest can help you make your profile more attractive to prospective employers. However, it’s just one piece of the engineering talent puzzle. 

    Related: Code Your Career: Staying Competitive in the Developer Job Market (VIDEO) 

    In addition to more granularity about coding languages and their competitiveness, the 2023 State of Software Engineers report dives into top roles, market trends, and salaries. The research gives you a better overview of:

    The state of the market

    Where the market is going

    How to best tailor your experiences and skills

    Originally written by Napala Pratini in March 2019. Updated by Hired Content Team in October 2023. More

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    Ready to Start Programming with AI? A Quick Guide for Software Engineers

    Though we’re still a ways out from building machines that will take over the world with artificial superintelligence, AI is on the rise. To sum up the recent explosion of generative AI, Vijay Pande, a general partner at venture capital firm Andreessen Horowitz, tells the Washington Post:

    “There’s a lot of excitement about AI right now. The technology has… gone from being cute and interesting to where actually [people] can see it being deployed.”

    AI has found its way into a myriad of applications (think: innovative approaches to coding reviews, testing, debugging) and is quickly becoming an advantage for staying competitive. Talent will likely be expected to leverage AI tools in their workflows to be more effective and efficient. In fact, the US Bureau of Labor Statistics shows that 37% of job descriptions listed AI work and skills in the emerging tech category. 

    This includes building programs to understand and help us humans in our day-to-day lives, like Siri, Alexa, and countless chatbots. It can make operations networks, like Amazon’s, hyper-efficient by predicting who will want what, when and where. It can also focus on research, with programmed learning able to evaluate results against hypotheses, and adjust and retest to advance our understanding of the world.

    Tip: Try some courses on AI and Machine Learning

    If nothing else, having some familiarity with AI could give you some Thanksgiving dinner fodder to blow your grandparents’ minds. But it also could lead to promising new career opportunities.

    Why AI?

    If you’re looking to add to your repertoire to boost your marketability as a software engineer, artificial intelligence is a safe bet. According to Hired’s 2023 State of Software Engineers report, demand for machine learning and data engineers ranks among the hottest software engineering roles.

    Here are a few lucrative roles for which AI programming may get you noticed:

    The other reason for picking this up is pretty simple: it’s cool as hell!

    The field of artificial intelligence is an exercise in replicating the very thing that (most of us would consider) makes us human. The emergent property of our trillions of synapses firing in a symphony gives me the sense that I am “me,” and each of you the sense that you are “you.”

    Though most applications facilitate learning-focused, singular tasks or making predictions based on massive data sets, there is still something special about working to bring machines to recreate biological capabilities. And even in weak AI, the possibilities are endless to help the world become a better place with creative, elegant software. And isn’t that what we all want?

    How to start programming with AI

    When it comes to picking the right language to get your career on an AI track, you need to decide what type of work you want to be doing and evaluate that against the support and pre-built libraries that can assist you along the way.

    Start with a general language that works well with data processing and analysis. The most prominent and in-demand at tech companies are Python, Java (or Scala), or R (if you exclusively want to be a data scientist). Choose just one.

    Learn a language for interacting with a database management system (DBMS) that will help you access and organize the data you’ll use in your algorithms. Knowing SQL and understanding basic NoSQL is highly recommended. If entering a larger company, Hadoop, Spark, or similar will also be helpful.

    Understand the key frameworks and libraries for building AI solutions. Some that are important for common AI problems are:

    TensorFlow (a must!): used for high-volume, complex numerical computations used for things like classification, regression, and clustering

    Caffe: used for image recognition

    Scikit-learn: used for common AI problems and data mining

    NLTK: used for natural language processing

    Try online courses for programming with AI

    It’s also helpful to experiment with the growing AI packages provided by online course providers like Coursera.

    Getting started with AI

    Getting deeper into machine learning:

    And some additional resources:

    Like any new skill, it will take discipline to master programming with AI. But from the practical to the theoretical, from the present to the future: programming with AI is a worthy practice to add to your tool belt.

    Originally written by Mike Parker in May 2019. Updated by Hired Content Team and Coursera in October 2023. More

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    Tech Roles on the Rise! What Tech Roles Increased Most in Demand in 2023?

    As technology and modern needs evolve, specific tech roles have risen in demand on the Hired tech recruitment platform. In Hired’s 2023 State of Tech Salaries report we revealed the top five in-demand roles “biggest movers” and why employers need them. 
    They are (in order of growth from 2022 to mid-2023): 

    Security (Cybersecurity) Engineer – Up 28%
    Data Engineer – Up 21%
    Machine Learning Engineer – Up 16%
    Business Analyst – Up 15%
    Backend Engineer – Up 11%

    1. Security or Cybersecurity Engineer
    Average interview request salary* on Hired: $165,003
    As the world continues to digitally transform, so do criminals. All kinds of businesses, in a variety of industries, have learned, some the hard way, how important security and cybersecurity engineers are to them. 
    In one example, patients of a Louisville, KY, hospital network struggled to obtain prescriptions and make appointments after a cyberattack stole personally identifiable information, (PII) and medical records. The ransomware disrupted patient care as well as set off an identity theft nightmare for the victims.  
    Employers generally prefer a degree in cybersecurity, computer science, information systems, or related fields. They may also look for practical experience building test networks or system prototypes. 
    Top skills employers look for in security engineers
    Ranked by priority in positions created on the Hired talent marketplace:


    *Average interview request salary means the average salary offer submitted by employers when they request an interview with a candidate on the Hired technical recruiting marketplace. Disclosing the salary for the role is part of the transparency we require of employers on the tech hiring platform. Jobseekers are required to list their salary expectations in their profiles. Combined, this helps drive better matches and an efficient hiring process for both tech candidates and hiring managers. 
    2. Data Engineer
    Average interview request salary on Hired: $163,782
    Modern companies rely on data about themselves, their customers, and their competitors to stay relevant and ahead. Data engineers are the architects who establish the structure to retrieve, store, and manage vast reservoirs of data. With a blend of software engineering and data-centric skills, they transform raw data into usable systems.
    Employers generally prefer a degree in computer science or related fields. They’ll also look for experiences displaying an aptitude for various programs, languages, and tools. Knowledge may include building data structures, managing databases, using big data, and how proper data infrastructure can affect a business.
    Top skills employers look for in security engineers
    Ranked by priority in positions created on the Hired talent marketplace:


    3. Machine Learning Engineer
    Average interview request salary on Hired: $169,666
    A machine learning engineer is a visionary technologist, harnessing the power of algorithms to teach machines how to learn from and act on data. These engineers are adept at creating technologies embedded with AI. Common examples of what machine learning engineers work on include self-driving cars for Uber and programming tailored search results for Google users.
    Employers generally prefer a Bachelor’s and Master’s or Ph.D. in computer science, an engineering discipline, or mathematics. They will also likely look for experience in working on practical and theoretical models.
    Top skills employers look for in security engineers
    Ranked by priority in positions created on the Hired talent marketplace:

    Natural language processing (NLP)
    Deep Learning
    Computer Vision

    4. Business Analyst
    Average interview request salary on Hired: $123,220
    A business analyst connects business objectives to technical solutions. With a sharp analytical mind and a keen understanding of organizational needs, they delve into business processes, identifying inefficiencies and opportunities for improvement. Business analysts gather and interpret data, translate business requirements into technical specifications, and work closely with stakeholders to implement changes that drive business growth.
    Employers generally prefer a degree in business administration, computer science, or related fields. They will also likely look for experience with business process modeling, data analysis tools, project management, and domain expertise. 
    Top skills employers look for in business analysts

    Data Analysis
    Microsoft Excel
    Data Warehousing
    Financial Modeling

    5. Backend Engineer
    Average interview request salary on Hired: $160,039
    While users interact with the visual elements of an application, it’s the backend engineer who ensures that data flows, servers respond, and business logic executes seamlessly. They design, implement, and manage databases, application servers, and API integrations. Backend engineers enjoy coding and crafting the foundation of successful digital experiences, ensuring performance, security, and scalability.
    Employers generally prefer a degree in computer science, software engineering, computer security, or related fields. They may also look for experience with computer programming, REST-based services, cloud infrastructure, automated integration tests, accessing data on mainframes, and continuous integration.
    Top skills employers look for in backend engineers


    Employers’ demand for specific engineering and tech roles grows
    The Hired tech hiring platform showed the greatest volume of active positions belonged to: 

    Backend Engineer
    Full Stack Engineer
    Frontend Engineer
    Product Manager
    Data Engineer 

    These roles are comprehensive ones and are used by businesses of all sizes in a variety of ways. The 2023 State of Tech Salaries report showed how important specialization has become with the growth of employers seeking Security Engineers, Data Engineers, Machine Learning (ML) Engineers, and Backend Engineers. 
    The Business Analyst subrole under Data Analytics also demonstrated a significant rise in demand on the Hired talent marketplace. With the rise of data, businesses need someone to help them interpret it and recommend actions.

    AI Researchers (typically known as Research Scientists and Applied Scientists) continue to be in high demand from tech companies big and small. Rora reports that researchers are one of the few roles that continue to have significant negotiation leverage – where it’s still common for candidates to line up multiple job offers at the same time.
    While AI Research Scientists are their own function at companies, they most closely align with the Machine Learning Engineer category on Hired’s tech hiring platform.
    Roles dropping in demand the most from 2022 to mid-2023 were:

    Product Designer – Down 26% 
    UX Designer – Down 20%
    Visual/U! Designer – Down 18%
    Product Manager – Down 15%
    Mobile Engineer – Down 12%.

    The impact of GenAI on tech roles in demand in 2023
    Unless you’ve been living under a rock, you’re familiar with the onslaught of GenAI in the last year. It was even a major point of the 2023 strikes by writers and actors. With artificial intelligence applications as the tech du jour, more companies want engineers comfortable and ready to lead with it. They want more machine learning researchers and engineers to bring AI technology to their business.
    Hired’s partner, Rora, shared there’s been a 21% year-over-year increase in demand for AI professionals. This is due to more funding, advances in technology, and the development of new use cases. Similar to the appetite for Web3 and blockchain talent in early 2022, in 2023 companies are competitively paying experienced AI technologists to sign offers.

    As part of the State of Tech Salaries, we regularly survey tech employers and workers. We asked employers if employees who understood AI were considered more valuable. The majority, or 59%, said yes. 
    In August of 2023, roles in emerging technologies or emerging tech skills requirements were part of 23% of all tech job postings. 
    In addition, the US Bureau of Labor Statistics shared inside categories like emerging tech, 37% of tech role postings included AI work and skills. 
    Hiring candidates in AI-driven roles
    Like many terms, AI has become a bucket to describe advanced computing technologies. Whether you’re a hiring manager, a CEO, or manage talent acquisition, the need for AI support may vary widely from business to business. 
    Some companies will use AI to analyze data, build new models, or conduct research. Some will develop new products and tooling. Regardless of your need, look for candidates with transferable skills. 
    Look for lifelong learners – people who are genuinely curious and embrace flexibility. Because the space is so new, any involvement in open-source-related projects is also a good indication of the aptitude to “grow with it. 
    Staying up to date with the demands of the ebb and flow of the tech hiring market is critical. As AI has shown, change happens quickly. 

    Need to hire any of these tech roles growing in demand? Request a demo. More

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    Where Do Engineer Salaries Pay the Best (Highest) Standard of Living?

    Opportunity shifts from higher cost-of-living markets

    The rise in remote work prompted engineers and other tech workers to move, freeing many from higher cost-of-living (CoL) markets. Because an engineer’s salary goes farther in lower cost-of-living markets, tech workers are reconsidering where to live. 

    Hired data in the 2023 State of Tech Salaries showed positions based in higher CoL cities continued to decline from 78% in 2020 to 59% in the first half of 2023. Unsurprisingly, San Francisco (one of the priciest markets to live in) saw the biggest decline change. Positions based there were cut in half. They dropped from 38% in 2020 to 19% in the first half of 2023.

    Medium CoL markets gained the most, expanding from 20% of positions in 2020 to 32% in the first half of 2023. Lower CoL markets increased from 2% in 2020 to 9% in the first half of 2023. While mid-market’s growth of 12% is higher, it’s worth nothing lower CoL markets more than quadrupled their previous percentage.

    Average software engineer salary offers

    Here’s the list of average salary offers made to software engineers on the Hired platform in 2023 (compared to 2022):

    SF Bay Area: $186,629 (up 4%)

    San Diego: $174,643 (up 20%)

    Seattle: $171,314 (up 1%)

    Los Angeles: $162,471 (up 2.5%)

    New York: $159,847 (down 1%)

    Boston: $156,510 (up 1%)

    Washington DC: $153,412 (up 1%)

    Austin: $150,246 (down 5%)

    Denver: $149,883 (up 0%)

    Philadelphia: $144,911 (down 0%)

    Dallas/Ft Worth: $139,742 (down 4%)

    Chicago: $138,795 (down 2%)

    Atlanta: $135,240 (down 8.5%)

    Houston: $134,711 (down 8.5%)

    Tampa: $129,323 (down 10%)

    Columbus: $128,854 (down 2%)

    The draw of lower cost-of-living markets 

    While it’s useful to compare top offers in top cities, these average offer numbers are most compelling in the context of actual living expenses. For instance, what does a salary of $149,000 actually get you in Atlanta? And what would you need to earn in San Francisco dollars to maintain the same standard of living? This is where it gets really interesting.

    After the CoL adjustment, most major metros offer more than their counterparts in San Francisco and New York City.

    When you compare city-specific salary offer data with the actual cost of living in San Francisco, surprising winners emerge. Namely: Houston, Atlanta, Philadelphia, and Phoenix where tech professionals are offered an average of $40K more than those in San Francisco. Unfortunately, New York is the only place where adjusted tech salaries are less than in San Francisco. 

    These adjusted salaries tell us a few things about the cost of living in each city, and where salaries might help you afford more in one city than another. 

    Sign up to join Hired’s talent marketplace and find a new engineering role. It’s totally free for jobseekers!

    Average software engineer salary offers — in SF dollars

    Houston: $228,000

    Atlanta: $227,000

    Philadelphia: $223,000

    Phoenix: $218,000

    Denver: $217,000

    Austin: $210,000

    Dallas/Ft Worth: $209,000

    Chicago: $201,000

    Los Angeles: $199,000

    Seattle: $196,000

    San Diego: $195,000

    Tampa: $193,000

    Boston: $191,000

    Washington DC: $190,000

    New York: $156,000

    [Tweet “TL;DR: Let’s all move to Houston.”]

    In all seriousness, these adjusted salaries tell us a few things about the cost of living in each city, and where salaries might help you afford more in one city than in other cities. (Read how C2ER’s Cost of Living Index is calculated here). 

    Here’s a breakdown of average salary offers, average/median living expenses, and other metrics that might affect your quality of life, by some example cities:


    Average software engineer salary offer: $137,000

    Average monthly rent for a 1 bedroom apartment: $1,087

    Median home price: $370,650


    Average software engineer salary offer: $149,000

    Average monthly rent for a 1 bedroom apartment: $1,507

    Median home price: $485,182


    Average software engineer salary offer: $151,000

    Average monthly rent for a 1 bedroom apartment: $1,138

    Median home price: $450,913


    Average software engineer salary offer: $140,000

    Average monthly rent for a 1 bedroom apartment: $1,179

    Median home price: $559,132

    Sources: Apartment List, PayScale

    Originally published in September 2016 by Whitney Ricketts. Updated by Hired Content Team September 2023. More

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    Hiring a Data Analyst? What to Look for in Top Candidates Now

    Hiring the right data analyst is crucial for your business. It’s like having a skilled navigator on your journey—it helps you steer your ship through the vast ocean of information. From enhancing marketing strategies to predicting market trends and even advancing healthcare, data analysis plays a central role in decision-making across various sectors.
    But what qualities does a data analyst need to possess? That’s exactly what we’re going to find out in this guide.
    The growing importance of data analysis
    Data analysis isn’t just an optional tool; it’s become a cornerstone of modern operations. 
    The global big data analytics market is worth $307.52 billion and is projected to hit $745.15 billion by 2030—a 13.5% CAGR. But why is data so crucial?

    Data from Fortune Business Insights
    Similar to having a trustworthy GPS system, data directs enterprises toward their objectives. Analytics does this by revealing trends and vital information that allow businesses to make important short and long-term decisions. 
    This is why hiring the right person for your data analytics role is so important.
    The impact of hiring the right data analyst
    Think of hiring the right data analyst as selecting an experienced captain for your expedition. The captain should be capable of providing solutions when you need them the most. 
    For instance, in times of crisis, such as tech layoffs, hiring the right data analyst who aligns with your company’s values is crucial. The analyst will help you determine how the proposed layoffs may affect the organization’s productivity and morale. 
    Here are four key benefits of hiring the right data analyst:

    Improved Decision-Making: A competent data analyst lowers your risk of making ill-informed decisions by offering insightful data analysis.
    Enhanced Efficiency: They are able to streamline procedures and spot opportunities for improvement, ultimately saving time and money.
    Competitive Advantage: With the right data analyst, your organization can gain a competitive edge by staying ahead of market trends and customer preferences.
    Innovation: Data analysts can find opportunities and patterns that are hidden and lead to new ideas within your company.

    The essential qualities of a data analyst: Technical skills
    There are four main areas to concentrate on when it comes to the technical side of being a data analyst. These skills are the nuts and bolts that allow your data analyst to navigate the data landscape effectively. 
    1. Working knowledge of data analysis tools
    Your data analyst should be well-versed in using software and tools specifically designed for data analysis. For instance, your company could be using a Vonage VoIP for small business system that generates a wealth of data on call volumes, call durations, and customer interactions. 
    Familiarity with tools like Excel, Python, R, or specialized software like Tableau is essential to uncovering insights. These insights can go on to drive significant positive results for your business. For example, by adopting Tableau, PepsiCo was able to reduce the time it takes to produce reports by up to 90%. 
    Related: Hired’s 2023 State of Tech Salaries report

    Data from Tableau
    Data analysis tools help in cleaning, processing, and transforming raw data into meaningful insights. For instance, when dealing with sales data, proficiency in tools like Excel can help identify trends and patterns in revenue generation.
    2. Programming skills
    Programming skills are the coding language that data speaks. A competent data analyst should have a working knowledge of programming languages like Python or R. They can perform sophisticated data manipulation and statistical analysis thanks to these languages. 
    For instance, when analyzing customer data for an e-commerce business, programming skills enable the automation of repetitive tasks, such as calculating purchase trends.
    3. Database management
    Databases are like the library of your organization’s data. Data analysts need to be adept at managing and querying data from various databases. Knowledge of SQL (Structured Query Language) is invaluable here, as it helps retrieve specific data from large datasets efficiently. 
    For example, when working with customer databases, a data analyst may use SQL to extract information about customer demographics and preferences.
    4. Data visualization expertise
    Data visualization is the art of turning numbers and statistics into visually appealing and understandable graphics. A proficient data analyst should be skilled in creating charts, graphs, and interactive dashboards. 
    Tools like Tableau, Power BI, or even Python libraries like Matplotlib and Seaborn come in handy here. When presenting quarterly sales reports to a team, data visualization expertise makes it easier for everyone to grasp the key insights at a glance.
    Note that recruitment tech like applicant tracking systems (ATS) can efficiently source and filter candidates based on specific criteria, including data visualization expertise. These systems can help you find data analysts with relevant skills and experience in this specific area, allowing you to narrow down your pool of candidates to the best ones.
    The essential qualities of a data analyst: Soft skills
    Soft skills are the intangible qualities that make a data analyst not just effective but exceptional. They enable the analyst to navigate the human and organizational aspects of data analysis, making a real impact. 
    1. Teamwork
    Because they frequently work in groups, it’s essential for data analysts to have strong collaboration skills. For instance, your marketing team may need to launch a retargeting strategy for e-commerce. 
    Such a strategy would require insights into audience segmentation, ad performance, and customer behavior patterns, which data analysts can provide. A data analyst with poor teamwork skills would hamper the success of the retargeting campaign. 
    2. Adaptability
    Analysts need to stay current with the continuously changing data landscape. Adaptability ensures that analysts can thrive in a dynamic environment. For instance, when working on a project where the data source suddenly changes, an adaptable data analyst can quickly adjust their approach to maintain data integrity.
    3. Communication skills
    Free to use image sourced from Unsplash
    Imagine having an excellent idea but being unable to communicate it; you won’t get very far. Data analysts need to communicate their findings effectively, both to technical and non-technical stakeholders. 
    They should be able to translate complex data into plain language and compelling visuals. This skill is crucial when presenting market insights to a group of executives or explaining data-driven recommendations to a customer.
    4. Analytical skills
    When it comes to finding hidden patterns and insights inside data, a data analyst needs to be a skilled investigator. They ought to be adept at analyzing intricate data sets, identifying patterns, and coming to insightful conclusions. 
    Consider a scenario where a company has implemented call center cloud solutions to handle customer inquiries and complaints. Without skilled data analysts, the wealth of data generated by these interactions remains untapped.
    5. Problem-solving abilities
    Data analysis often involves resolving complex issues. Your data analyst should have a knack for approaching problems methodically. They should be able to break down large, intricate challenges into smaller, manageable parts. 
    When a retail company, for instance, has to determine why its sales have declined in a particular area and how to reverse the trend, this quality is vital.
    6. Attention to detail
    Data analysts should be meticulous in data collection, cleaning, and analysis to ensure accuracy. When, for instance, a financial institution is auditing transactions, attention to detail is essential to spot anomalies that could indicate fraudulent activities.
    Other important factors to consider when hiring a data analyst
    When searching for the right data analyst, their experience and specialization are vital aspects to consider. These factors ensure they can effectively navigate the specific challenges your organization faces. 
    1. Years of experience
    While years of experience alone aren’t the only indicator of a great data analyst, they do matter. 
    More experienced analysts often possess a better understanding of cutting-edge methods and proven problem-solving abilities. 
    For instance, when dealing with historical market data, an analyst with several years of experience may have insights into market cycles that a less experienced analyst might miss.
    2. Industry specialization
    An analyst with industry specialization has an in-depth understanding of specific sectors. For example, a call center utilizing auto-dialing software will benefit from hiring a data analyst with experience in the call center industry. 
    Such an analyst would be skilled at identifying specific call dispositions that lead to successful outcomes and recommending strategies for tailoring auto-dialing scripts to maximize results.
    3. Project portfolio
    Think of a data analyst’s project portfolio as their resume in action. It’s a collection of past projects they’ve tackled, showcasing their ability to deliver results. 
    For instance, a data analyst’s portfolio might include projects where they improved supply chain efficiency, optimized marketing campaigns, identified cost-saving opportunities, or analyzed the traffic of an OnlyDomains website. By looking at their portfolio, you’ll be able to better gauge whether their past expertise is a good fit for your company.
    Hiring a data analyst with confidence
    With the ever-increasing prominence of big data, working with a skilled data analyst is paramount for businesses across all sectors.
    A well-rounded data analyst should demonstrate a special mix of abilities, knowledge, and experience. Use the tips listed above to make the right choice when hiring tech talent for your business. 
    Remember that recruiting the right data analyst is more than just filling a job vacancy; they are a calculated investment in your success in the future. More