“I’d like to see more focus on using AI, analytics and data science for social good. It could have such a huge impact on the world.”
Rachit Khare has spent the last decade working at the cutting edge of data science. He talks to us about the aspects of his job that keep him interested, and how the technologies he works with could go on to change the world.
A happy accident
Like many of our data scientists, Rachit has always been interested in numbers. But to begin with at least, analytics wasn’t really on his radar. Or anyone else’s for that matter.
“When I started out, this wasn’t a massive field in India,” he says. “But, coming from an engineering background, it was quite easy to transition into the developing world of analytics – and exciting to be able to relate maths and science to real world problems.”
Thankfully for Rachit, what was then a sort of misunderstood offshoot of business intelligence went on to become big business in its own right. But, as he points out, perhaps a more interesting question than ‘how did you get here?’ is ‘why are you still here?’ What keeps someone interested in crunching numbers for over ten years?
“Analytics is really rewarding if you’re a logic-driven person,” he says. “If you enjoy problem-solving and if you hate repetition, it’s great. I may have been doing this for ten years, but every day is a new challenge – I’m always kept on my toes.”
An amalgamation of skills
As a relatively new field, data science is evolving far faster than most industries. Seeing those changes unfolding first-hand means the job never gets stale.
“I think analytics is always changing because it’s a convergence of so many different disciplines,” Rachit says. “You have elements of applied statistics, mathematics, operations research, data engineering, computer science, software development and, increasingly, design thinking. And then, when you’ve got all these things in a big melting pot, you have to think about how you can apply them to solve a business problem.”
In his day-to-day work with The Smart Cube, Rachit works directly with our clients to help them get the most value from this melting pot.
“My role sits within the client solutions team,” he says. “I’m positioned at the intersection of business, technology and analytics, and tasked with bringing those elements together to help solve our clients’ challenges.”
The reward of results
Despite every job being different, there’s one thing they all have in common – and for Rachit, it’s the most rewarding part of his job.
“I love that you can actually see our contribution clearly, by drawing a line from where our client started to where we’ve ended up,” he says.
As an example, Rachit recalls a recent, multi-year project with a leading European retailer.
“This was a top five company in its sector,” he says. “But in terms of analytics they were behind the curve; relying on a big Business Intelligence team to churn out thousands of reports with limited application of advanced analytics.”
Through a series of small wins, each working towards a grand vision, Rachit and his team worked with the retailer to transform their approach to analytics.
“We worked with our client to adopt agile analytics delivery methods. The goals was to move away from big, bulky multi-year transformation projects, with renewed focus on frequent value release through each iteration.” he says. “This is great, as it cements their trust in us, but it’s also really rewarding for us to see the positive commercial and operational impact of our work each step of the way.”
Gradually, this approach led to a cultural shift within the retailer, symbolised by the transformation of its old-school Business Intelligence team into an ‘Advanced Analytics Centre of Excellence’.
“In the end, I think for every pound the company invested in their analytics projects, they got more than 10 back,” Rachit says.
Here’s to tomorrow
After ten years in the industry, Rachit has seen a great deal of change, and expects to see a lot more in the coming years. He cites deep learning as one example; a technology that has made previously out-of-reach use cases not only feasible but commercially scalable, too.
Perhaps the greatest progress in this area has been in the machine perception field, with technologies like computer vision, speech recognition and natural language processing.
However, to really reach the next level of what is possible – to move beyond mere perception into the realms of logic, reasoning and imagination, Rachit believes there will have to be a step-change in technology as a whole.
“Deep learning is fundamentally data and computation hungry,” he says. “We’re reaching the higher echelons of Moore’s Law with regards to processing power. There’s only so much you can fit on a chip, and the carbon footprint of doing really complex deep learning would be huge using our current technology.”
The good news is, researchers are already seriously pursuing the next game-changer, with significant funding from top tech firms.
“Quantum computing could fundamentally change how all of this works,” he continues. “Though it’s in a very nascent stage at this point, the next decade or two could see it move from an experimental to a commercial technology.”
Although, as Rachit points out, it’s not just technology that has to progress for us to meaningfully attempt Artificial General Intelligence.
“The algorithms we use will have to significantly evolve, too,” he says. “After all, the human mind is far more complex, yet many times more efficient, than any current AI algorithms.”
A better, happier, healthier society
What’s likely to happen next in the world of data science is one thing. But perhaps a more pertinent question is what would Rachit like to see happen.
“Personally, I’d like to see more focus on using AI for social and environmental causes,” he says. “A lot of money goes into commercial applications, but if you just look at some of the ways people are using these capabilities to help less fortunate people, it’s amazing what we could achieve.”
As an example, Rachit cites one Google project currently using AI to identify early stages of preventable blindness in India. He also has an admiration for the work of Bill Gates, who writes often about how technology can help solve the world’s humanitarian issues, from climate change to child nutrition.
“As AI and machine learning evolves, it can help us tackle some of our toughest challenges in healthcare, climate change, and education,” Rachit says. “And I’d like to see us, as a society, focus on this a lot more.”
Rachit’s recommended reading:
- MIT Technology Review