Instinctive Racing
Jun 12, 2019

The yin and yang of being a data scientist

Meet the team behind our work with Formula E team Envision Racing

A candid conversation with Sahil Makkar, senior data scientist, Genpact, about changing career paths and being a part of the Genpact-Envision Racing partnership.

Sahil started his professional journey as a computer engineer before discovering his love for AI seven years ago, which led him to change his career path. "My passion for math pushed me toward AI," he says. Today, he uses his expertise to enhance prediction with AI and help estimate how many laps there will be in a Formula E race, which is important information for the team to strategize their moves.

When your passion becomes your job

"My role at Genpact has turned my fascination with AI into my profession. And getting to work with the Envision Racing team means there's double the excitement!" he tells me.

Winning on a Formula E track depends on many factors. An important one being how much energy a car uses during the race's 45 minutes (plus one lap) – the team can't underutilize or overutilize its battery power. To help Envision Racing enhance energy management for its cars, Genpact has developed the Lap Estimate Optimizer. Our solution is a deep learning system that houses different algorithms that not only detect patterns but also improve existing models, helping the team predict lap numbers and shape race strategy.

“Our focus is on estimating the number of laps accurately and analyzing behaviors of different drivers to improve performance. The advantage of a strategic project like this is that you get to see how your work blends with Envision Racing's expertise and existing systems to influence the race outcome," says Sahil.

About the author

Simon Fellowes

Simon Fellowes

Genpact trackside reporter

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