Retaining your Data Science Teams
-Kumar Metlapalli, Founder & CEO Kuberre Systems
April 28, 2021
Data Scientists, and other employees with quantitative analysis skillsets, require special care in order to retain them for the long-term. They are motivated by lifelong learning opportunities, exposure to promising new technologies and the ability to feel the impact of their work. Our first-hand experiences with customers shows us that these employees represent the “secret sauce” to the investment operation as they are charged with the job of Alpha discovery. The future of the firm depends on the quant team’s ability to create and realize outcomes from the gems hiding in large/complex data sets. These folks are hard to find and demand premium salaries. Losing and replacing quant talent is a risky and expensive game to play.
Why the sensitivity? Data science is a specialty with a dependence on incredibly deep mathematics backgrounds. The best of the best carrying advanced degrees from elite institutions. It takes incredibly focused effort to recruit and onboard talent for the reasons mentioned above. Once they are a part of the organization, and have become fully engrained in the operation, it is critical that the investment be protected like any other in the portfolio.
The good news is that retaining team members with these quantitative skills is relatively straight forward. Being one myself, I can tell you that we always want to learn and solve new/challenging problems. But in the workplace that requires a few extras. The obvious is that they need to feel the respect of their peers. In most instances I would say there is a very healthy respect for the value my quant friends bring to the table. The next one is to respect their time and effort. This one is a bit more complicated. Because they want to perform and create outcomes… it can be extremely frustrating if the path to results includes too much low-level effort. They don’t want to spend their day writing APIs, linking databases or otherwise engineering data pathways in order to interrogate the data. These are all necessary evils along the journey. Organizations can protect the morale of the team, and efficiently drive results, by bringing in the right technologies and partners to lift that burden. Add in cutting-edge analytical technologies and we will have created a great retention story.
While I was putting my notes together for this post I came across an interesting article by Sarah Butcher entitled “Why quants quit jobs in investment banks” (https://news.efinancialcareers.com/us-en/3002121/quant-jobs-investment-banks). The article highlighted observations of people like Daniel Rosengarten, head of asset liability management quantitative development with Barclays, as he noted, ”if you want to see a quant go crazy, give them a large amount of data, and Excel to work with it”. Apurv Jain, visiting researcher at Harvard University, noted that “Cleaning the data is 80% to 90% of the work and most people don’t feel like doing that.” With these realities in play, it is no wonder quants may make the shift back toward academia or to firms that offer them the ability to focus on the rewarding work. Not the torturous effort of transforming a “data swamp” (Rosengarten’s term) into a usable data lake.
Within our company here at Kuberre, and with nearly all of the firms we have worked with over our 20 year history, we have seen it all. The ones that prioritize retaining their staff enjoy a long track record of results by surrounding their teams with leading tech, opportunities to continue learning, mentors, opportunities to showcase their successes and offer them the ability to squarely focus their attention on getting to meaningful results. At our company we use this perspective as we design and deliver our software/services. We then encourage our clients to fully leverage the retention benefits our tech and data leaders have to offer to their teams. When we are successful, our company enjoys more dynamic client relationships and our clients enjoy the improved outcomes that come from happy-motivated data science teams.
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Article referenced above: https://news.efinancialcareers.com/us-en/3002121/quant-jobs-investment-banks