Interview Log: A Day in the Life of the Head of Data Science

Data science is a buzzword in the tech world, promising lucrative salaries and great job growth. It is one of the most rewarding and sought-after careers today. It is equally challenging. Data scientists require in-depth knowledge of computer technology, programming languages, software, and analytics to work with large amounts of data.

We interviewed Aditya Agarwal, Head of Data Science (Practice Lead) at Abzooba to learn about the skills and experiences to be a successful Data Scientist. He specializes across a range of domains including Business Analytics, Statistical Modeling, Predictive Modelling, and Project Management. Aditya holds a Bachelor of Technology and a Minor Degree in Business Management from the Indian Institute of Technology (IIT), Delhi.

His valuable insights will guide you to start a career in the data science field.  

Valuable Insights For Data Science Aspirants By Aditya Agarwal 

Q1. Please share a brief introduction about your role as Head of Data Science (Practice Lead) at Abzooba.

Mr. Aditya: I have 13+ years of experience working in the data science domain, of which, I have spent nearly 7 years with Abzooba. At Abzooba, I am leading  Advanced Analytics (AA) Practice, working with 60+ energetic data scientists on a variety of problem statements across insurance, retail and healthcare domains, using tabular and text data both.

My responsibility is to grow the practice by nurturing and mentoring the talent, keeping team knowledge and skillset updated with the emerging market trends, explore new data science capabilities and in turn deliver high-quality solutions to our clients.

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Q2. What’s your job like? Is there a typical day or is each day different?

Mr. Aditya: My daily job requires a lot of collaboration with clients, the pre-sales team,  data scientists, data engineering and quality assurance team members to meet the delivery deadlines with utmost quality. I do spend a good amount of time evangelizing the advanced analytics practice through self-initiated projects, learning new technologies, sharing best practices and knowledge between project teams and many more. In short, each day comes with new learnings.

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Q3. Please shed some light on your career path and how you started your career in data science and grew to your current role of Head of Data Science?

Mr. Aditya: I started my career as a data scientist at one of India’s leading life insurance companies. At the start of my career, I got the opportunity to work with a highly passionate and energetic team, and with highly qualified mentors. My mentors always focused on me to learn the applicability of data-driven solutions to solve business problems along with data science skills. This experience helped me to bridge the gap between the non-tech business team and core tech teams. With time, technologies kept changing but the core data science concepts and the business problems remain the same. Constantly upgrading my skillset and learning new technologies helped me to cover the journey to grow to my current position.

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Q4. What types of career opportunities are available in the field of data science? Could you please share some insights?

Mr. Aditya: With the advancement in the data science field, there are varied opportunities available in this field. One can pursue as a researcher where a researcher will be working on proving a hypothesis, solving open data science problems,  or improving existing solutions using a new algorithm, etc. On the other end, one can pursue an Applied Data Scientist. An applied data scientist uses existing algorithms to solve business problems. 

At Abzooba, we focus mainly on applied data science. There are different roles available within applied data science and one can choose based on his taste and likings. One can master working with one or more types of datasets like tabular, text, audio, images, videos using statistical learning or/and deep learning. 

Q5. With 10+ years of industry experience, according to you, what skills or characteristics make someone a seasoned data scientist?

Mr. Aditya: A seasoned data scientist needs to wear multiple hats – while being a good data scientist, he should be a good communicator, a good collaborator, and more importantly a good data engineer. He should be able to work with end-to-end Machine Learning applications i.e. from setting up of data pipeline to operationalization and monitoring of the models. 

With all the above skills, a sense of being responsible and a good mentor are most important to be a seasoned data scientist.

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Q6. Which educational background do you hold? How has this education helped you in career growth?

Mr. Aditya: I am an engineer and hold B.Tech in Textile Technology from IIT Delhi. I also pursued a minor degree in Business Management from IIT Delhi. My specialization during college and data science does not have much in common, however, our curriculum at college widens our quantitative skills and aptitude to solve problems. During academia, reading research papers, writing a thesis teaches us to implement research papers and perform experiments. These skills really helped me to understand and implement complex concepts of data science in real business problems.

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Q7. How do you keep yourself skilled and relevant in terms of knowledge?

Mr. Aditya: In the data science world, learning new skills is not an option, it’s a mandate. In the last 5 years, favorite tools and technologies for a data scientist are completely changed. I devote few hours every week to my learning and development activities without any fail.

Q8. Which certification courses, skill development paths, books, or channels do you recommend to those who are planning to enter the data science field?

Mr. Aditya: Today, one has numerous options of courses and books for data science. One should really take a pause, define the scope and stick to a plan. I advice 

1. Choose an open-source language like Python or R, grab basic concepts with the help of a book. I find O’Reilly published books are really good, comes with practice datasets and code.
2. Choose a basic machine learning course before jumping to deep learning. One can choose Udemy, Coursera, Simplilearn to understand the concepts and do not forget to practice hands-on.

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Q9. What does the future of Data Science look like?

Mr. Aditya: With the advancement of technology, reduction in the cost of hardware, and increase in data volume and variety, I see the adoption of data science across businesses will go high. A lot of data-driven solutions like language models, text generators, Question and Answering models, etc that were not thought of a few years back are becoming readily available to use. This whole data science ecosystem is moving more towards 2 streams – one that research and create algorithms, and another that apply these algorithms to solve business problems. This keeps happening and machines and businesses will become smarter and smarter.

Q10. Concluding words – What’s the best piece of advice you would give to our readers?

Based on my experience, I can advice

1. Learning should never stop. 
2. Mentoring someone is the best way to learn for yourself.
3. Communication of insights from data science algorithms to a business stakeholder is very important to grow to the next step of your career. 

Conclusion

Starting a career in data science may seem challenging. All you need is proper guidance  to start your journey. You can get the most valuable information to get started and become a successful data scientist through this path. 

Check out the popular Data Science Courses on Shiksha Online to become a Data Science expert. These courses will help you to gain in-depth knowledge about the most advanced data science skills through online lectures, case studies, projects, practical hands-on workshops, and guidance from industry experts.

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