CDO: Sameer Gupta, Point72

1. Tell us about your career and what brought you to your current company.

I trained as a computer scientist in college and have spent my entire career in financial services. I have a competitive nature, and I’ve always liked the industry because it’s hyper-competitive, too. Finance companies tend to invest heavily in innovation to stay at the forefront, which also appeals to me.

Throughout my career, I’ve worked for different types of finance firms, from a hedge fund, investment banks and a stock exchange to an AI startup. That has enabled me to learn a diverse set of skills including sales, product management, technology, operations and finance, all as they relate to capital markets. Having that diverse background also helps me understand how companies operate and how to use data to identify competitive advantages. In addition, my technology background helps me use powerful tools (e.g., Cloud Computing) to quickly identify efficient solutions to problems.

Point72 is a global hedge fund that prides itself on applying innovative techniques to asset management as we seek to achieve superior returns for our investors. Point72 is also unique when it comes to Wall Street firms in the value that we place on having an entrepreneurial mindset. I first learned about Point72 when I was building iSentium and was in contact with Pete Casella, a partner in Point72 Ventures’ Fintech practice. Pete later went on to introduce me to an opportunity in the Market Intelligence group within Point72.

2. What are the projects you are most excited or proud about?

I believe that skills-based learning is going to continue to play an important role in education, and free online learning platforms like Coursera and Kaggle will enable individuals to gain relevant skills in technology and data science, irrespective of their backgrounds.

At Point72, we recently led an initiative with Google for City University of New York (CUNY) students. We invited a group of 100 students to learn about the role of data and analytics in investment management in a monthlong program where students tried to predict restaurant grades in New York City. Students worked in teams, met with Point72 and industry professionals for advice, and learned to apply machine-learning techniques on Kaggle to solve the problem. For me, the most gratifying part of the experience was when one of the students from the program was hired by Point72.

3. What are the toughest challenges you have experienced regarding handling data or digital transformation? 

There are two big challenges, one that is more widely common to companies across industries and another that is more finance-specific.

First, for a lot of companies, the design of a typical organization is one of the biggest barriers to improving their digital systems. If you think about conventional organizational design, you have functions like sales, product management, operations, technology, finance, and human resources, all as separate silos with limited or no visibility across them. This structure worked for decades because information flow across business units was often limited and there was not much need for tighter integration. As organizations have become more digital, information flow within silos is getting much faster but there are more bottlenecks sharing information between silos. Those bottlenecks include disparate technology between departments and business lines, data architectures that prevent tighter integration, and lack of expertise and business understanding across different business units. On the other hand, successful companies have addressed this problem by using data holistically. For example, companies like Amazon and Netflix are using data to procure the right mix of products, price goods and services competitively, help consumers find the right product at the right time, and ultimately deliver that product to customers at the click of a button.

Second, looking specifically at financial services, the interoperability (or lack thereof) of data across different sources for the same entity continues to be a big issue. For example, a publicly traded company can have different unique identifiers as you move from one data source to another. This can be particularly problematic when you enter the world of alternative data that contains individual brands and businesses. For this data to be actionable, brands and businesses need to be accurately tied back to actual companies.

4. When you think about a few years from now, what will be the biggest changes we will see regarding data management in organization?

I can see a scenario where data management gets very sophisticated and interdisciplinary, and where traditional business functions will join forces with data and technology groups. Up until now, we have seen management at some companies focus too much on artificial intelligence and machine learning, while data management has largely been ignored. As AI projects fail to deliver on the hype, there is likely to be a greater effort made to ensure the AI models are being fed correct and relevant data. Data management is very complex and can’t be done properly unless it is really understood well. The most successful companies will be the ones who create interdisciplinary teams that understand, maintain and leverage data better than any standalone team of data or technology professionals.

At Point72, we approach data management as a critical and integral part of our business, and our researchers and data professionals work closely to integrate data into the investment process.

5. We all have experienced some dramatic changes and challenges in the past few months due to the COVID-19 pandemic. How did the pandemic impact your company?

Like most other companies, the immediate impact was that we transitioned to working from home. I found it impressive how well Point72 adjusted to the change, and I think we have been able to sustain, if not increase, our productivity levels.

While we haven’t been able to interact in person, we’ve really emphasized strong communication and transparency, which, in turn, makes work more meaningful for everyone.

Personally speaking, I’m fortunate that working from home has allowed me to accelerate learning new skills and applying them directly through deep and uninterrupted work.

6. How is data being used to help with these challenges? 

Our firm relies on data analysis when making business decisions and investment decisions. Having that infrastructure already in place gave us an advantage as we navigated volatile market conditions this year. We also have a strong culture of innovation that helps us be nimble and efficient in consuming and analyzing new types of data to better understand a fast-changing world.

7. How do you learn about new technologies? What makes you try a new technology?

Growing up, I was always curious and passionate about learning, and that passion has stayed with me as an adult. As new technologies continue to emerge and drive disruption across industries, I continue to have a drive to learn about them quickly and apply them when appropriate.

I think when you’re trying to learn any new technology, it helps to have a problem in hand because you can test the technology by trying to solve that problem, which enables you to learn through observations and iterations. I also like to learn from companies that are bringing these technologies to market so I can keep on the cutting edge of innovation.

SAMEER GUPTA BIO

Sameer Gupta is the Head of Data for the Fusion business at Point72. His group is responsible for the identification, acquisition, onboarding, and distribution of data for use in the investment process. Previously, he managed the Data Sourcing team for the Proprietary Research business at Point72.

Before joining Point72, Gupta was the chief operating officer at iSentium, an artificial intelligence startup where he led key business functions including sales, business development, fundraising, engineering, and operations. Before iSentium, he was the COO for the Global Electronic Trading and Americas Cash Equities business at JPMorgan. Gupta also served in business development and product management roles at New York Stock Exchange Technologies, and in software development and technology strategy positions at Goldman Sachs. He is also actively involved in the New York City startup community through TechStars and New York University’s Endless Frontier Labs.

Gupta earned his MBA from Harvard Business School, M.S. in Information Systems Management from Carnegie Mellon, and B.S. in Computer Science from the National Institute of Technology in India.