investment banks vs retail banks and the data science race







These are certainly interesting times for all involved in the global sphere of data science and none more so than within the world of banking. Within such a complex and diverse industry there are many moving parts across multiple sectors, making it more challenging for experts to spot trends. With this not only comes uncertainty but anticipation about the potential that lies within for many top-tier banks. However there is one trend in particular that has elevated to the forefront of data science. Investment banks are playing a game of catch-up whilst the candidate job market continues to gather pace.

Today most retail banks have mastered the art of leveraging the use of data science, by analyzing customer behavior and predicating which customers are most likely to default on credit cards; as well as identifying potentially fraudulent transactions. As a result, this provides a data science workload, driving the need for a retail bank to invest heavily in modern technology and recruit personnel.

Many of the top-tier retail banks are mirroring the technological advancements of the global insurance and management consultancy sectors, by creating data science groups housing predictive modelers and machine learning experts. These groups then act as an internal resource of intelligence; aiding data-driven decision making across the organization.

It is one thing identifying the need to invest aggressively in modern technology and personnel, although there are only a select few top-tier banks who have successfully executed such a strategy. There are only a select few top-tier banks who have successfully executed such a strategy. It is only a matter of time before others follow suit and begin to gather deeper customer intelligence, and realize the tangible, quantifiable benefits at stake for the entire organization going forward.



Growing Importance of Data Science

As for investment banks, substantial consideration must be given to fact that they currently struggle to determine what beneficial data science use-cases exist within their business model. Undoubtedly this issue will continue going forward into the next quarter.

The demise of the Wall Street boom-era left many investment banks in a perilous condition and those still standing have done remarkably well to stabilize. However only a fool would underestimate the beast that lies within investment banks, in the form of huge potential relevant to spending power and intelligent strategists. Once valid use-cases are identified and streamlined, then the hard-push will begin to catch up with retail banks.

During this state of industry flux, we at Harnham have witnessed notable developments taking place within the data science candidate market. As the demand for us to supply quality personnel intensifies, the job market has become more competitive than ever for candidates and employers alike.

This has led Harnham to open an office in New York City, as it is undoubtedly the banking & financial services stronghold of the United States. With this, comes the powerful status of being the most competitive data science job market in the world. Equally this creates a number of problems, yet a number of advantages for those operating within this space.

 

Banking on Life Long Learning

One trend in particular has seen quants, reared in the traditional banking world of Wall Street, who then seek a career path towards modern data science falter; as such a move means utilizing unknown technology and software packages.  These candidates now face increasing difficulty making this transition internally due to a lack of modern skills.

Their woes are further compounded when entering the job market, as most are leaving roles at investment banks with the same technology skill-set they acquired many years ago. With that said, all is not lost as there are an abundance of online data science courses now available at prodigious universities such as Harvard, allowing skill-short candidates an opportunity to get to grips with modern programming languages such as Python or R etc. and big data packages such as the Hadoop platform.

Furthermore the emergence of data science boot-camps such as the Metis Boot-Camp (an immersive Data Science boot-camp in New York City) and Columbia University offer a Master’s Degree in Statistics, with focus on data science and machine learning; provide an alternative option. Many job seekers have gone as far as ceasing employment to join such boot-camps. Some have gone a step further still, by going back to university and undertaking a Masters in a data science related field.

As a result of this movement in the candidate market, there is a tug-of-war taking place between those coming from the top universities with Masters or PhD qualifications and those leaving the investment banks searching for data science roles on the retail side.

 

The Winner Takes It All

Who gets hired, all boils down to a question of each individual banks requirements and which skills they deem as the most important - domain expertise and practical experience verses a highly accomplished modern data science skill-set. Those who combine the two will naturally be more competitive in their search and overall more enticing to potential employers.

From a positive perspective, despite the barriers to entry mentioned, we are right in the midst of a data science market that is actively evolving all the time. It is fast paced, dynamic, exciting and full of opportunity on all fronts.

Given the lean years we have experienced, this is an exciting market to be part of and one that will be at the forefront of a data and analytics evolution, which will grow exponentially over the next five years and beyond.

   Allister Duncan
 

Harnham blog & news

With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.

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Leading Remote Teams in the Land of Beer, Barbeque, and Tech

Charlotte, North Carolina known for its beer and barbeque is not the first location to jump to mind when you think digital hub. But here’s the rub, it is. In the Fall of 2019, the city and Microsoft signed a three-year digital alliance. And as the country moved from office locations to work-from-home and remote operations, Charlotte became a prime destination for tech.  Four Skills for Leading in the New Normal Whether you’ve learned to balance work time with virtual schooling or have been working from home for years, there are some skillsets which set leaders apart. The first one may surprise you. Let others lead – According to our most recent salary guide, one of the main reasons people leave their jobs is due to poor management. With the rise of remote working, hierarchy has flattened to a degree as everyone must discipline themselves. Micromanagement becomes almost moot as everyone leans into this learning curve. Lead by example and let others take over the leadership driver’s seat from time-to-time. Balance both Soft and Technical Skills – While technical skills are the backbone of subject matter experience in a Digital Analytics role, it’s the soft skills which can help set you apart. Sure, you’ll want to know the ins and outs of web analytics and optimization, but you’ll also need to have the skills to explain findings and offer recommendations to address client needs. Know When to Pivot – Life throws us curveballs. Consider 2020, for example. Whether you must pivot for survival or simply need to take things in a new direction, knowing when to pivot and how to explain it to your employees is a leadership skill inherent for this new normal. Be Approachable – With open door policies moved online, leaders will want to determine the best way to recreate opportunities for employees that need to talk outside the daily or weekly staff meeting. Having insight into how your team works best, can help you guide them toward success. Programs to know and experience to have often include the technical knowledge you’ll need to ensure your client makes the most informed decisions.  ‘Smart Cities’ of the Future At the beginning of 2020, as the coronavirus came to call, someone joked that in 2020 we’d hoped to have flying cars and smart cities of the future, but instead were being taught how to wash our hands. Perhaps they weren’t far off on the smart cities quip as both Houston, Texas and Charlotte, North Carolina are on the cutting edge of creating these smart cities. Things like Massive Open Online Courses (MOOCs), LinkedIn Learning, even the Entrepreneur Store offers classes and bundles in everything from computer language learning such as C++, R, and Python to Digital Marketing and Graphic Design. But, learning these things and more on a Microsoft campus can catapult students into more jobs and helps guide cities in smart power grids, smart busses, autonomous cars, and the list goes on. Experience in a design agency who works within both the B2C and the B2B verticals helps to expand opportunities exponentially. Remote working opportunities have opened up worlds of collaboration, teamwork, and focus on the next steps into the future. Whether you’re interested in a remote working leadership role in the beachy Carolinas or looking for your first or next role in Big Data, Web Analytics, Marketing & Insight, Life Science Analytics, and more, check out our current vacancies or contact one of our recruitment consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Career Priorities Are Shifting For The US Data & Analytics Market Place

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Navigating the New Normal Now and In the Future

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How Digital Analytics & Marketing Help Shape E-Commerce

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