Description of Current Work

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Q: Can you describe your current position, and what field or space you work in?

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A: So currently, I'm working as a senior data scientist at S&P Global here in New York. This is a financial services company, and what the company does is extract knowledge from all sources of data to gain insights into the financial world. Being part of a data science team, we assist other product teams to derive these insights using AI-based technologies.

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Typical Daily Tasks

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Q: What does a normal day look like for you?

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A: AI-based teams are mostly project-based, so day-to-day tasks change after a span of time when you start working on something new. We’re not directly in operations or maintenance. We research new projects and products, and currently, we’re working a lot on Gen AI. On a daily basis, we have different products where we want to incorporate AI and Gen AI. Part of the day is dedicated to R&D, and the rest is spent creating code to apply these cutting-edge technologies into our products. So, it’s a lot of coding, a lot of meetings, and a lot of research.

 

Career Path

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Q: Can you give us a quick overview of your career journey, including your education and previous jobs?

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A: I am an electrical engineer by background. I did a bachelor’s in electrical engineering in Pakistan, where I’m originally from. After that, I worked for a couple of years in engineering and project management. Then I saw how AI was rapidly evolving, so I decided to pursue a master’s in AI from the University of Bologna in Italy. While studying there, I worked at a startup and interned at BMW in Munich, Germany. After that, I moved to the U.S. to work at S&P Global, where I’ve been for about three years. Alongside this, I’m pursuing an MBA in finance and strategic management because I’m now more interested in financial services.

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Emerging Career Opportunities

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Q: In your current field, what do you think are the most interesting career opportunities emerging in the next 5–10 years?

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A: With tools like ChatGPT, writing code is becoming a commodity—anyone can prompt a model to write code. The most important skill in the coming years will be problem-solving ability—the cognitive skill to analyze what you want to achieve and then design a solution using various tools, including AI. Once you know what you want, achieving it will be easier, but designing the right solution will remain critical. You’ll still need to learn fundamentals, especially in computer science, to use these tools effectively and improve efficiency.

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Advice for Aspiring Data Scientists

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Q: Do you have any specific advice for a young person interested in your field?

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A: Have a passion for continuous learning. In the past, major revolutions like the industrial or agricultural revolutions took decades to unfold. Now, technologies can become obsolete in just a couple of years. To succeed, you must be flexible and open to learning skills you didn’t know yesterday. In data science and AI, new tools are released daily—you need to learn, grasp, and use them effectively in your work.

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Career Reflections

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Q: Is there anything you would have done differently in your career journey?

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A: I would have gone into AI much sooner. I spent the first few years of my career outside AI, but looking back, I wish I had entered the field earlier. It’s intellectually challenging and offers great opportunities for growth.

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Why the Career is Cutting-Edge

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Q: Why would you consider your career cutting-edge?

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A: Every major industry is moving toward AI. Whether it’s financial services, retail, or restaurants, companies are incorporating AI into their products, and this is just the beginning. The amount of R&D in this field, the rapid improvement in computing resources like GPUs, and the investment from top global stakeholders all make AI a cutting-edge technology right now.

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Career Goals

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Q: What are your short- and long-term goals?

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A: My short-term goal is to stay ahead of the curve by adapting to new technologies and continuing to learn, like I am now with my MBA. Long-term, I want to use these technologies to develop a product that benefits everyday people, not just corporations. I believe we should democratize technology so it serves the common person.

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Intersection of Data Science and Finance

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Q: How do your interests in finance and data science intersect?

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A: Data science skills are tools for analyzing data and extracting insights, but understanding the domain is just as important. At BMW, I learned as much as I could about cars; in healthcare, you’d learn about pharmaceuticals. In financial services, I’m building my finance knowledge so I can interpret financial data effectively. Data science and domain expertise go hand-in-hand.

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Importance of Learning to Code

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Q: With AI models able to write code, is it still important to learn programming?

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A: Absolutely. If you don’t know the fundamentals, you can’t validate whether an AI-generated answer is correct. Knowing programming and computer science basics allows you to evaluate and guide AI outputs, develop guardrails, and interact effectively with these tools.

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We would like to thank Mr. Razzaq for the time he spent speaking with us, and we hope you were able to learn something from the insight he provided.

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From,
Cooper