At our recent Leading with Data session, we were delighted to welcome Aamod Sathe, a data science and analytics leader with almost two decades of experience. Currently, Aamod leads the MetaWorks analytics team at Reality Labs at Meta, where he helps build the metaverse and the future of work. With a solid background in mathematics, statistics, and engineering, Aamod offers valuable insights into the world of data science and its applications in business. From his trip to the field to his thoughts on the future of data-driven businesses, Aamod shared his experience and wisdom with our audience.
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Let's see the details of our conversation with Aamod Sathe!
Key insights from our conversation with Aamod Sathe
- A solid foundation in mathematics and statistics is crucial for a career in data science.
- The application of ai in business should be driven by the specific problems it can solve, not just the technology itself.
- Company culture plays an important role in the success of data science initiatives.
- Intellectual curiosity and the ability to ask the right questions are key traits for successful data scientists.
- Generative ai will enhance the role of data scientists by automating routine tasks, but human-centric skills will remain irreplaceable.
- Executive engagement is essential to driving change in data culture within organizations.
- Startups that are tackling complex problems with artificial intelligence and technology, such as space technology and climate technology, are particularly interesting for future growth and innovation.
How did your journey into data science and analytics begin?
My journey into data science and analytics is a combination of meticulous planning, preparation, and a good dose of luck. Being in the right place at the right time played a crucial role. My academic background laid the foundation and my master's research in neural networks laid the foundation for my interest in data science. Over time, as the field matured, my career evolved from analytics to the specialized domain of data science.
Before data science, what was your focus?
In the beginning, I was more mathematically inclined and had a strong engineering background. As I progressed through my master's degree, my natural inclination towards statistics and data science became evident. My master's thesis involved the use of neural networks to optimize the location of emergency vehicles, which was a clear indication of my interest in this field.
<h2 class="wp-block-heading" id="h-can-you-describe-the-evolution-of-ai-and-data-science-in-your-career”>Can you describe the evolution of ai and data science in your career?
My career began with roles heavily focused on modeling, such as fraud detection on eBay. Over time, the business problems we sought to solve dictated the scope of ai application. While ai is a powerful tool, it is essential to use it appropriately depending on the business context. Early in your career, it is beneficial to be practical and theoretical, as opportunities to explore broadly decrease as you specialize.
At Meta, I lead a data science team within Reality Labs, focusing on MetaWorks. We apply AR and VR technology to business solutions. My role involves driving product decisions through data science and representing the voice of all data functions, from core data science to sales and marketing analytics.
What cultural trends define the success of data-driven companies?
Company culture is an important determinant of a data scientist's success. Companies like PayPal and Meta, where I've worked, are leaders in leveraging data and putting data professionals at the decision-making table. A culture where data wins arguments is crucial to the effective application of data science.
What traits do you look for when hiring data scientists?
Beyond essential technical skills, intellectual curiosity and the ability to ask the right questions are vital. Organizational skills and the ability to build relationships across teams are also crucial, as data scientists often need to influence decisions without direct authority.
<h2 class="wp-block-heading" id="h-how-has-generative-ai-impacted-your-work-and-what-s-your-take-on-its-future”>How has generative ai impacted your work and what is your opinion on its future?
Generative ai has made it urgent to leverage ai technology in business. While I am excited about the potential of ai, I believe we will experience a typical product curve and eventually adapt to practical applications after the initial hype. Ethical considerations, policies and privacy will play an important role in the future of ai.
<h2 class="wp-block-heading" id="h-how-will-generative-ai-change-the-life-of-a-data-scientist”>How will generative ai change the life of a data scientist?
Generative ai will enhance, rather than replace, the roles of data scientists. Routine tasks and experiment setup could be automated, allowing data scientists to focus on more complex, non-repetitive problems. However, skills like organizational influence and converting business problems into data problems will remain human-centric.
What advice would you give to drive change in data culture?
Driving change in data culture requires buy-in from executives and careful selection of battles. Early wins with clear data-driven results can help influence processes and establish data-driven decision making. However, it is essential to recognize when to drive change and when to adapt to the existing culture.
What excites you about advising startups and what problems do you hope will be solved?
Mentoring startups, especially in India, is incredibly rewarding. I'm excited about startups tackling space technology, artificial intelligence, agriculture, and climate technology. Robotics, transportation and climate solutions are areas where I expect to see significant advances, leveraging ai to address large-scale challenges.
summarizing
Our session with Aamod Sathe offered a wealth of insights and inspiration for anyone aspiring to lead with data. With his extensive experience and leadership in data science and analytics, Aamod emphasized the importance of a solid foundation in mathematics and statistics, as well as intellectual curiosity and the ability to ask the right questions.
He offered a realistic perspective on the evolution of ai, highlighting its potential to enhance the functions of data scientists by automating routine tasks, while underlining the enduring importance of human-centered skills. His mentorship of startups, particularly in India, showcases his passion for fostering innovation and driving data-driven decision making across industries. We appreciate Aamod's valuable contributions to this session and his continued impact on the field of data science.
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