With over eight years of experience increasing growth, productivity, and efficiency at prestigious organizations like HSBC, American Express, Capital One, and Lyft, Saurabh Kumar is a Lead Data Scientist at Apple. At Apple, he concentrates on experimentation and machine learning (ML) to enhance the Ads marketplace.
Among Saurabh’s many academic accomplishments are degrees from Columbia University and IIT Kanpur, one of the best engineering schools in India with a highly selective 1% admittance rate. His knowledge encompasses significant data ecosystems, machine learning, data structures, algorithms, economics, soft skills, and business intuition developed via training at Columbia Business School and practical experiences.
Data Science Expert – Saurabh Kumar
A passion for leveraging data to solve practical issues led Saurabh to pursue a career in data science and technology. Early stints at NASA and Deloitte Consulting gave me a strong foundation in using my analytical talents to solve challenging problems. His career began in the banking industry, where he held American Express and HSBC positions.
There, he honed his grasp of data-driven decision-making in giant corporations. His employment with Capital One, where he worked on initiatives to promote financial access for marginalized populations, was a turning point in his career. Saurabh demonstrated his dedication to using data science for social benefit by assisting in expanding financial access for students and immigrants by utilizing alternate data sources for credit scoring models.
At Lyft, Saurabh served as Head of TBS Payments Data Science, focusing on fraud reduction and improving customer experience in the ride-sharing industry. His current role at Apple involves pioneering experimentation and ML techniques to optimize the Apple Ads Platform, impacting millions of users worldwide. What sets Saurabh’s story apart is his consistent focus on impactful data science applications, from financial inclusion and fraud prevention to enhancing user experiences across various industries.
Challenges and Solutions
Throughout his career, Saurabh has faced significant challenges. At Lyft, he collaborated with stakeholders to define clear, actionable payment health metrics, employing statistical and ML techniques to identify failure causes from comprehensive data. He designed a user-centric, real-time dashboard highlighting key metrics and trends, implemented quick solutions for immediate improvements, and conducted A/B testing to validate their effectiveness.
At Apple, Saurabh tackled bias in experimentation by developing a budget split design to mitigate bias from shared advertiser budgets. He conducted simulations to secure the design, effectively reduced bias, tailored complex designs to different engineering teams, and emphasized overall experiment validity and business outcomes to secure stakeholder buy-in.
Saurabh’s Advice
As Saurabh has learned, clear communication is crucial for effective collaboration and problem-solving. Engaging with diverse teams provides broad perspectives and data-driven decision-making with incredible accuracy. He emphasizes the importance of agility, user-centric design, and continuous learning.
His advice to others includes communicating complex ideas simply, tailoring messages to the audience, engaging actively with diverse teams, relying on data for decisions, staying flexible, focusing on user needs in design, and committing to lifelong learning.
What the Future Holds
Saurabh envisions continuing to innovate and lead in data science, particularly at the intersection of machine learning and experimentation. He aims to advance to a strategic leadership role, mentor the next generation of data scientists, and contribute to projects that leverage data for significant societal impact. Saurabh aspires to be a thought leader, pushing the boundaries of what data science can achieve and driving technological advancements that improve lives.
