Carson Boneck, chief data officer, Balyasny Asset Management

What are your key areas of focus for data and analytics in 2022? 

The financial industry is extremely competitive, and, at its core, finance is a talent industry. Talent is always my primary focus; building an environment where our A-players can lead the way, solve hard problems and have agency over their careers and professional development.

Along with talent, you must get the engineering right. We do not talk AI and ML to have more buzzwords to share; our focus is on consistent improvement through technology to earn the right to take more experimental shots on goal. Pragmatism always beats the buzz when it comes to data.

Tell us what leadership means to you in the context of your role as a senior data leader. 

To be a great chief data officer, one must be comfortable with rapid context switching and operating at all levels of the organization. My job is not to report on the work of all the smart people on my team, but rather to put them into those conversation directly. I think great leaders realize that they are stewards of talent. We are continually asking ourselves where we can drive deeper business value and competitive advantage. 

I am fortunate to work at a firm where the chief data officer has a seat at the table, alongside a great technology organization. I think all financial firms will arrive at a similar construct, if they have not already, given the rise in alternative data and the merging of quantitative and traditional investment styles.

And what about the skills of your data teams and of your business stakeholders? How are you developing data literacy across the company/organisation? 

Our focus has evolved over time and as our firm’s needs have changed. In the early years we largely focused on the blocking and tackling of data — data platform and distribution, governance, etc. We were largely servicing requests from our key stakeholders and building foundational architecture.

Fast forward a few years and our focus evolved into continuing to advance our platform and deepen our understanding of where we could drive value. This has meant the formation of various data management and data science teams to work with our investors. We also created an online data catalogue to aid in data discovery across the firm.

Data literacy is not an aim in and of itself but rather a means to an end. In our team’s case, the goal is to help our investment teams make better investment decisions. Therefore, we must be willing to say when data should or should not be used. I believe it takes collaboration, open-mindedness, humility, grit and objectivity to be great in data. The job is never done and that is what makes it so exciting.