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Inside Analytics: Meet the Data Scientist Q+A: Balasundar B, Data Science team lead

Our Data Science team lead, Balasundar B, discusses his journey to The Smart Cube, and the work that’s been happening in our AI Lab since he joined.

Since The Smart Cube’s AI Lab launched last year, the team has gone from strength to strength, adding new experts to its ranks and finding powerful real-world applications for some of the most promising new AI algorithms and capabilities.

One of the most recent additions to the Lab is Balasundar B, who joined us to lead our Data Science team in 2022.

We recently caught up with Balasundar to learn more about his experience, what attracted him to The Smart Cube, and the great work that’s going on within its AI Lab.

Q: Bala, thanks for joining us. Could you start by telling us a little about your background in the AI field?

Balasundar: I’ve been working in the data and AI space for more than 12 years. I started my career as a .Net developer in an IT service company, which is where I first became fascinated with the potential of AI. We initially explored AI and Machine Learning as a potential solution to some of the data-related challenges the company was facing, and I was immediately taken in by its potential.

I have an interest in mathematics, an area that didn’t feature heavily in the first few years of my career. AI and ML brought mathematics back into my working life, combining it with my technical expertise to create an emerging field that immediately felt like a natural fit for me. From there I started focusing all my efforts on this space, and haven’t looked back since. 

Q: What led you to The Smart Cube, and why was it the right next step in your career?

Balasundar: The biggest reason why I wanted to join The Smart Cube was that the company shares my enthusiasm for AI, and most importantly has the right kind of experimental, leading approach to it that I wanted in an employer. 

AI Lab is a huge part of that. Being able to experiment freely with new algorithms and align emerging techniques with emerging business challenges is really exciting. At The Smart Cube, this isn’t just theoretical, we’re committing to discovering what works, so that we can deliver high-value, leading AI solutions to our clients.

Q: Since becoming a major part of our AI Lab, how have you found the experience?

Balasundar: Firstly, the onboarding experience has been great. I’m part of a new wave of SmartCubers that work remotely. It wasn’t just good compared to other remote onboarding experiences, either – it was the smoothest transition I’ve ever had into a new role.

Despite being based in a different city, I’ve been integrated into the team very well. It’s been incredibly easy to communicate and collaborate with people, and even though we’ve only physically met a few times, we’re able to work together smoothly and seamlessly.

The AI Lab is also a great thing to be a part of. We’re constantly bringing in new ideas from data scientists from across the company and client organisations to be part of our experiments and bring fresh perspectives and insights to them. They get the chance to be part of the lab’s leading work, and we all get the chance to collaborate with new people. It helps create a culture where everyone is continuously developing, taking on new tasks and learning from one another.

Q: The AI Lab has been up and running for over a year now. Can you tell us about some of the capabilities and use cases the team has been experimenting with recently?

Balasundar: We’re continuously undertaking new experiments based on our observations of the challenges our clients are facing, and new capabilities and algorithms that we see emerge. 

Our combination of deep AI expertise and our close relationships on the ground with our clients enable us to work in an extremely interesting space, where we’re essentially matching emerging business challenges up with emerging AI capabilities and algorithms. We follow The Smart Cube’s ethos of combining AI and Human Intelligence to build powerful solutions to real business challenges, and ultimately improve the working lives of the people we serve.

Recently, two major areas that we’ve been focusing on are Explainable AI and Natural Language Generation (NLG). Explainable AI is hugely valuable in areas like healthcare, where doctors can use it to better understand and verify AI-generated diagnoses and care suggestions. Similarly, it’s also being applied in highly regulated spaces like financial services to help teams clearly report on their AI models, inputs, and outputs..

NLG is creating opportunities for organisations to not only understand the sentiment of complex documents and recorded speech – it’s converting it into clear, summarised, and entirely new text. That has a wealth of applications too.

Q: Is your work in those areas still limited to experiments, or are you seeing it cross over into live work with The Smart Cube’s clients? 

Balasundar: That’s the great thing about the AI Lab. First, we get to prove an algorithm’s ability to solve a specific business challenge in theory – then we get to put it into practice. 

Just recently, one of The Smart Cube’s large pharmaceutical clients came to us looking for help understanding and summarising hundreds of complex documents. Using models we’d already built in our experiments, we were able to distil those documents into one- or two-page summaries of entirely new content – all generated by AI.

Q: What do you think the future of AI holds, and what are you most excited about as you look ahead to the rest of your journey with The Smart Cube and our AI Lab?

Balasundar: As AI becomes stronger, more transparent, and more trusted, a huge range of new use cases are going to emerge. AI has always had the power to transform data-intensive areas like medical research and drug discovery. But now, advances like explainable AI are helping to remove barriers like low transparency that have prevented many organisations from applying AI in those kinds of sensitive areas where recommendations and decisions impact human lives and wellbeing.

The volume and variety of data available to businesses is also set to continue growing sharply, which will have a big impact on AI use cases like personalisation and dynamic consumer recommendations. As organisations augment their models with new and larger data sets, they’ll be able to get even deeper with how they personalise customer experiences and journeys.

Those are both areas we’ll be keeping a close eye on within the AI Lab, but looking to the future, we’ve got some more ambitious plans for experimentation too. Today, we’re focused on matching emerging AI techniques and capabilities with emerging business challenges.  

When our clients want to take steps to adopt new technologies, we need to anticipate their needs, and ensure that we can help them apply AI in the right ways, within those new digital contexts. That’s a hugely exciting space, and one where our work is going to be right on the bleeding edge of innovation. Watch this space.

Find out more about The Smart Cube’s AI Lab, and how our experiments and research are delivering strong results for our clients.

  • Jenny Rushforth

    Jenny is responsible for managing all of The Smart Cube’s marketing content, collateral and external communications programmes. Jenny has over twenty years’ experience in the fields of PR, marcomms and analyst relations, across a range of sectors from Healthcare to Financial Services. When not working, she loves spending time with her husband and hamster, cooking new recipes, reading and trying to keep up with Netflix.

  • Jenny Rushforth

    Jenny is responsible for managing all of The Smart Cube’s marketing content, collateral and external communications programmes. Jenny has over twenty years’ experience in the fields of PR, marcomms and analyst relations, across a range of sectors from Healthcare to Financial Services. When not working, she loves spending time with her husband and hamster, cooking new recipes, reading and trying to keep up with Netflix.