To say there is a massive buzz around data science would be captioning the obvious. The overwhelming amount of resources and information resulting from the rapid evolution of the field could leave an aspirant at sixes and seven.
Analytics India Magazine caught up with Dr Angshuman Ghosh, Head of Data Science at Sony Research India, to understand his thought processes and gain insights into the inner workings of the emerging field of data science. He has over 12 years of experience in Technology, Media, and Retail companies, such as Disney, Target, Grab, and Wipro. He is an Official Member and Contributor at the Forbes Technology Council and a visiting professor at top IITs, IIMs, and XLRI.
AIM: Could you talk about Sony Research India and your role there?
Dr Ghosh: Sony Research India (SRI) is the research and development arm of Sony Global in India. SRI was established in 2020 and part of the global R&D of Sony. With SRI, Sony seeks to accelerate research, collaboration, and innovation capabilities in India. Sony Research decided to venture into India due to its growing economic potential and the high availability of skilled professionals.
I joined SRI in October 2020 and was the first recruit for this unit. I lead the overall data science department in SRI. We are currently focusing on Sony’s India entertainment business, including its TV channels and the OTT platform. We are pumped about the OTT channel SonyLiv.
Being part of the leadership team, I am also quite involved in the talent acquisition and team-building process and hope to gradually build a strong team of professionals.
AIM: What are the tools and models used at SRI?
Dr Ghosh: We are quite a generalist in our approach when it comes to the tech stack. We are currently working with Python for programming. We are leveraging AWS for our cloud infrastructure needs.
We are also open to using several machine learning and deep learning methods, which will shape up in a much bigger way in the coming months.
AIM: What are the skills you look for while recruiting?
Dr Ghosh: I believe though the technology keeps evolving, few basics remain unchanged. Same with data science, for beginners, we expect them to have sound knowledge of statistics, probability, linear algebra, machine learning, etc. Python and SQL skills are also must-haves. However, we are flexible on the domain knowledge part, which we expect the candidate to pick up on the job.
Apart from these technical skills, we also give great preference to an aspirant’s attitude and general professional approach.
AIM: What motivated you to get into data science?
Dr Ghosh: To be honest, there wasn’t a definitive point when I decided to become a data scientist. I pursued computer science engineering and graduated in 2005. Soon after, I started working with Wipro, where my job primarily involved programming and software development for some of the Fortune 100 clients. Though I was technically sound, I realised the importance of understanding the business aspect of it.
My next natural step was to pursue an MBA, which I did from XLRI Jamshedpur, with specialisation in marketing and finance. Given my interest in research, I also decided to complete my PhD. During this time, I got a lot of background knowledge on statistics, regression, R and other tools. My PhD work was around deriving insights on user behaviour from what they post on social media.
In 2015, I joined Disney Star TV. My work was a mix of analytics and research.
That was also the time I started shifting to data science. I realised that my background aligned quite well with the requirements of the data science field. My shift to core data science was when I joined Target, a hotbed of data science developments.
AIM: What is your advice to students pursuing a career in Data Science?
Dr Ghosh: We can talk about different tools and methods for Data Science, but at its core, Data Science refers to using data, scientifically, to make decisions or make an impact.
There are three key skills for any data scientist– a stronghold on mathematics and statistics. Secondly, you need a programming language base for different tasks such as data processing, storage, etc. Lastly, domain knowledge. When you are working in a company, you must think about what value you are adding.
Having acquired these skills next comes constant upgradation and upskilling. There is a sea of resources available online. For example, Coursera and EDx are good sources for theoretical introductions to a variety of topics. For a more practical approach, aspirants may check Datacamp and Udemy. I would also suggest using Kaggle, participating in hackathons, and undertaking internships to gain an edge.
It is also important to think from the perspective of being ready for future challenges, given this field’s dynamic nature. It does get difficult to catch up with every new model or concept. I find it difficult too. What I tend to do is I try to look at the bigger picture, and once a tech starts picking pace, I spend time understanding it. The secret lies in following a broad macro trend, not just in DS but in complete tech space.
AIM: You offer a lot of mentoring through your social media posts. Do you think we should have more mentor-mentee approaches for the larger benefit of the ecosystem?
Dr Ghosh: It is my way of giving back. When I started, such blogs and resource material helped me a lot. I also do a bit of analysis to understand what kind of topics students might be interested in and try to give guidance.
Speaking of having such a mentor-mentee ecosystem, yes, it is ideal. Python grew so big because it has an extensive network of contributors and collaborators. That said, being a mentee is a personal choice. It can’t be forced on someone.
