Data Science is arguably one of the hottest topics across most industries nowadays – meet Vikas – Senior Data Science Manager – and learn about his personal journey, what makes a great data scientist, why Vista offers the perfect ground for growth and a lot more!
Meet Vikas Grover, senior manager in data science.
My name is Vikas Grover, and I currently serve as a Senior Manager of the Data Science (DS) Chapter in Vista DnA. Thanks to the amazing “Remote First” work policy at Vista, I am able to work from my home location in Gurgaon, India. I have done my Masters of Computer Technology from IIT Delhi with 10+ years of industry experience. Among my responsibilities at Vista DnA are overseeing DS work for exciting domains such as PPP (Pricing, Promotion, Personalization), FSD (Full Spectrum Design), and CBPM (Customer & Business Process Modelling), as well as fostering the career advancement of highly talented data scientists in these areas.
Was a career in data science a conscious choice? How did you end up choosing it?
I entered the Data Science field at a time when the term wasn’t so popular. I started my career as a software engineer, but it didn’t feel like a good fit for me. Luckily, I got an opportunity from American Express to work in a “business analyst” role where my responsibilities also involved building predictive models based on big data. I have never looked back since then. The change required much dedication to building a solid foundation in machine learning. Luckily significant learning happened in the workplace. My studies in computer science and ‘pattern recognition’ related courses taken as part of my master’s degree were a great help in the learning process.
Talk a bit about your personal journey in data science and how it’s evolved over time.
I started by building a solid foundation. As an individual contributor, I learned about machine learning concepts and algorithms and applied that knowledge appropriately in solving business problems. The experience of learning Python was love at first sight for me, and I did quite well with my tasks. While my background helped me develop technical skills quickly, I had to put extra effort into non-technical aspects like coherent story presentation, grasping complete business context, guiding fellow teammates, and the like. With time, these skills became more substantial, and I found myself absolutely loving mentoring others. This experience allowed me to grow into a manager role. This role presented an entirely different set of challenges—delivering high-quality work while managing everyone’s expectations was tough. Quite surprisingly, effective leadership was my passion, especially when it came to making the right decisions for my team. I enjoyed solving challenges by building trust-based relationships and empowering individuals. Today, nothing brings me more joy than contributing to others’ success.
What’s the best advice you have been given in your career? Why?
It’s cliche, but it’s mighty effective: “Never stop learning” is my mentor’s ‘holy grail’ advice. As you learn, you develop skillsets and knowledge, which in turn leads to confidence in your ability to do your job well. ‘What to learn’ varies throughout your career depending on your interests, role requirements, and time availability, but learning should never stop. As you gain experience, you need to identify efficient learning methods, which automatically happen when you have the right mindset.
What made you choose Vista as the next chapter in your professional career?
The people and the company culture—I highly value the people with whom I work because I believe you are shaped by the people with whom you spend most of your time interacting. In the interview process, the interactions and answers I got regarding team and company culture made me believe that this might be an opportunity for me to get my finest professional experience so far. As I enter my second year in my current position, I can easily say that my expectations have been exceeded. Working for Vista has indeed been the “best time of my professional life”.
What are the skills that make a great data scientist?
Data science is both an art and a science, and you need a mix of hard and soft skills to succeed. Here’s my take:
- Solid foundation in machine learning
- Expertise in programming,
- Maths and statistics,
- Business acumen and
- Effective communication.
Once solid foundations are built, I recommend that people double down on their strengths to carve out their own ‘great’ path.
Why should Data Scientists choose Vista as their next step?
Vista is a wonderful place to work. Interacting with talented and motivated team members is one of the most exciting things about working here.
The daily challenges provide people with great opportunities to dig deep into AI and ML concepts and boost their growth professionally and personally. As a data scientist, you can also witness ML concepts and data being translated into significant impact for our customers and share in Vista’s transformative journey. With its collaborative team culture, the leadership here is truly outstanding. The entry bar is high for obvious reasons, but if you possess the required skillset and attitude, it will be one of the most rewarding experiences of your professional life.
Customer obsession is a key element of DnA and Vista—how do you instill “customer obsession” in your team?
We always start from customer needs and work backward to find the best solutions. We always ask ourselves one question in all the tasks we take up, “How will this make the customers’ life easier or better?”. Constantly asking ourselves this question and having an unflinching focus on solving customer needs helps us instill an obsession to deliver outstanding value for our customers.
What do you find most interesting and inspiring about our customers?
At Vista, we serve the small businesses community, which we can all relate to and feel close to. Providing a platform where these small business owners can unleash their creativity is a significant driver of our function. Specifically, in data science, we work so customers can seamlessly find, design, and purchase their desired products.
To this effect, we have created multiple machine learning solutions to enhance customer site experience and personalization and provide a differentiated journey. To name a few, we have solutions that touch various aspects of the customer journey, such as sitewide search, ‘Next Best Action’, personalized recommendations and offers, price automation, and the like.
What aspect(s) of Data Science are you particularly interested in these days?
I am a huge proponent of a pragmatic mindset in data science. In applied DS, one rarely encounters ideal circumstances in the real world. Innumerable challenges are faced, such as data quality and availability, execution constraints, and the like. There are times when data scientists become too focused on providing the best ML solution without recognizing the ultimate goal: “To provide business impact”. In Vista, our general philosophy is “test and implement” to deliver maximum impact in an agile fashion. We keep reminding ourselves to take a step back and answer questions like
- “What is the overall potential business impact?”
- “Have we established a baseline?”
- “Is ML the best solution, and will a ‘good enough’ solution suffice?”
- “What is the quality of the data, and what can be done with the available data?”
- “How should we test our solution?”