At present, the unemployment rates in the U.S. are low. At the same time, the tech talent shortage has grown exponentially. According to the annual CIO Survey conducted by Harvey Nash and auditing firm KPMG, as much as 65% stated that hiring challenges were hurting the industry.

A decade ago, the perfect solution would have been the influx of foreign-born talent to fill the skills gap. But today, that’s no longer a viable option.

The Trump administration continues to tighten immigration controls, and temporary H-1B work visas for highly skilled professionals are now capped at 85,000 a year. That number doesn’t come close to matching the demands of the U.S. job market.

The FinTech industry is at the frontline of this fierce battle for the brightest minds in the business. For example, while 82% of companies plan to expand their workforce, 64% of them will have to contend with the skills gap.

This scenario has also had a considerable impact on the costs associated with recruitment delays. If you need ten software engineers, for example, and the recruitment cycle drags on for six months, your cost per hire will add up significantly. Here’s an example:

CPH = ($82,000+$35,000)/10=$11,700/person

Each extra day for hiring decreases on-job performance by 1%, according to HackerNoon.

It’s only going to get worse as experts estimate the demand for FinTech services to grow by a whopping compound annual growth rate (CAGR) of 25%-30% from 2019 to 2025. So you can expect the tech talent shortage to create significant barriers to innovation.

How Are American Companies Responding to the Talent Shortage?

As North American companies have to compete over a small pool of talent, they have had to get creative to try and differentiate themselves from the competition. 

Besides offering mouthwatering salaries and benefits packages, they have also had to engage in publicity stunts, offer crazy sign-on bonuses, and even sponsor professional events. 

However, while these techniques can pay off, it doesn’t guarantee recruitment success in the long-term or a positive return on investment. If you take a large event attended by potential candidates, for example, what’s the guarantee that you’ll ever hear from them again?

As a result, it’s safe to conclude that FinTech companies need to invest in building sustainable recruitment strategies that can keep potential candidates continuously engaged. 

They have also had some success hiring freelancers remotely leveraging the gig economy. But if you’re a startup racing toward a minimum viable product (MVP) or a minimum marketable product (MMP), this approach could be challenging to manage. 

Let’s take a look at what’s happening in FinTech hotspots across America.  

Silicon Valley is home to tech giants such as Apple, Facebook, and Google. The Bay Area is also home to leading FinTech startups like Blend, Coinbase, Nova Credit, Ripple, Stripe, and tons more. 

The third-largest and the most populous state in the U.S. has the economic resources and, of course, sunshine and picture-perfect coastlines to attract top talent. But, even here, the competition between multinationals and startups alike remains fierce. 

LinkedIn, for example, has almost 20,000 software engineer jobs currently listed on its job board. If we search for FinTech engineers, you’ll find more than a thousand vacancies in the Bay Area. 

So what kind of remuneration packages do the most in-demand FinTech skills command in San Francisco?

Tech Salaries In the Bay Area

Software Engineer

Software engineers in the Bay Area make an average of $150,000 a year. However, if you’re on the hunt for senior developers, that number can quickly rise to a mouthwatering $420,000 annually. 

Blockchain Engineer

According to Glassdoor, a blockchain engineer can earn anywhere from $50,000 (at an entry-level) to $250,000 a year. These salaries reflect not only the demand but also the high cost of living in the region.

Machine Learning Engineer

Machine learning engineers who are proficient in programming languages like Python, Java, Scala, Go, and C++ command an average salary of approximately  $130,000. 

When you add expertise in deploying large scale models using Scikit-learn, TensorFlow, Keras, Spark MLlib, PyTorch, MXNet, CNTK, and other libraries, it can quickly rise to $280,000.  

Deep Learning Engineer

Deep learning engineers in San Francisco can attract salaries that are over $250,000 a year. However, the average financial package is around $150,000 annually.

Data Scientist

There is a significant demand for data scientists in the Bay Area. So these FinTech professionals can command an average salary that can be as much as $350,000 a year.

When you think of technology hubs, Texas probably isn’t the first state that comes to mind. However, this southern state has managed to nurture a highly collaborative environment that has helped tech startups and FinTech companies thrive (especially in North Texas).

Texas is home to a significant number of Fortune 500 companies, so it makes sense that FinTech is starting to make a mark here. 

Some of the leading FinTech companies in Texas include:

• BankMD
• GigWage
• Honest Dollar (by Goldman Sachs)
• Modo

While the competition for tech talent is slightly less than in San Francisco, the shortage is impossible not to notice. Texas currently has over 17,000 software engineering-related vacancies on LinkedIn alone. 

So you can bet that top FinTech talent in the area will also command some of the best remuneration packages in the country.

Tech Salaries In Texas

Software Engineer

Mid-level software engineers in Texas earn approximately $75,000 on average. But if you’re looking to hire senior developers, that number can rise to $150,000 annually. 

Blockchain Engineer

According to Glassdoor, a blockchain engineer can earn anywhere from $43,000 to $191,000 a year. This reflects the fact that the demand for blockchain engineers isn’t as high as the Bay Area. 

Machine Learning Engineer

In Texas, the average starting salary for a mid-level computer vision engineer is about $80,000. This number can rapidly rise to $150,000 per annum when you consider their experience and present market demands.

Deep Learning Engineer

Deep learning engineers in North Texas command an average salary of $100,000 per annum. However, companies like Samsung Research America can pay as much as $142,000 a year. 

Data Scientist

According to Indeed, entry-level junior data scientists can earn about $50,000 a year. However, senior data scientists can command a yearly salary between $120,000 and $140,000. 

Up in the Midwest, Chicago is making waves with over 40 FinTech companies innovating and revolutionizing financial services. Some of these companies include Ansarada, Bento for Business, Braintree, and NextCapital.

It makes sense as the State of Illinois has a long history of banking and trading. This makes using technology as a tool to solve today’s problems the natural next step in the evolution of the industry.

At present, there are almost 9,000 vacancies in the State of Illinois, waiting to be filled by top tech talent.

Tech Salaries in Illinois

Software Engineer

In Chicago, software engineers earn about $75,000 on average. At the top end, it can rise to $290,000 a year. 

Blockchain Engineer

Blockchain engineers in Illinois earn around $75,000 a year on average. However, tech giants like IBM can offer more than $100,000 a year to an experienced blockchain engineer. 

Machine Learning Engineer

The average salary for a machine learning engineer in Illinois is about $80,000 annually. However, it’ll take a whopping $300,000 a year to attract senior machine learning engineers.   

Data Engineer

Although there isn’t a demand for deep learning engineers here, there is a significant demand for data engineers. In Chicago and the surrounding area, data engineers command a starting salary of around $75,000 a year. 

Data Scientist

Data scientists can earn an average salary of approximately $100,000 a year. However, if you browse through the vacancies, you will notice that there is an urgent need in the area to fill these positions. So that number can quickly surpass $150,000 a year.

As you can see from the above, FinTech startups and established companies have to expend a significant amount of resources to attract top talent. But even when they have funds to pay high wages, variables like location, weather, and family commitments can threaten to derail projects. 

Whenever this is the case, it’s better to embrace a FinTech software team extension model over traditional outsourcing. 

Team extension (aka Extended Team) makes sense because your in-house team will work in concert with your remote team. This approach ensures that you remain in control of your FinTech development projects. 

As a result, this development model is better than working with an outsourcing provider (that doesn’t keep you in the loop every step of the day) or freelancers (who tend to be committed to the highest bidder and not the project). 

Working with an extended team services provider in countries like Ukraine, for example, can be highly rewarding. This is because they have a large pool of highly-qualified talent that can be leveraged affordably (without compromising quality). 

To put this into perspective, consider the fact that this Eastern European nation churns out about 25,000 – 30,000 STEM graduates every year. 

The average annual salaries are also much lower in Ukraine for top FinTech talent. For example, an experienced FinTech software engineer in Ukraine commands an average annual salary of $40,000 (add 10-15% on top of that for Kyiv jobs). Unlike America, Ukrainian gross salaries already include social tax and benefits, so the total cost of your extended team will be up to 40% lower.

This model envisions transparent payroll: as a client, you get a monthly invoice comprised of each team member’s gross salary and your team provider’s management/hosting fee (fixed) per each person. This helps eliminate hidden agendas and overheads at a later stage of engagement and allows for more efficient resource planning.

Wrapping up, when extending your FinTech dev team, you get the following benefits:

So team extension with Ukrainian FinTech professionals can not only provide access to top talent but also help achieve your goals on time and on budget. 

At Evolve, we are experienced in building high performing Extended Teams that deliver award-winning FinTech software solutions. If you would like to learn more about our team extention services and our Ukraine-based R&D Centre, request a call back now!