As we move on in our journey of talking to industry experts from different domains to help job aspirants find the right career for themselves, this time we had a chance to interview Mr. Deep Sachdev, Data Science Manager – dunnhumby. An Analytics Professional, Deep has 10+ years of experience in the field of data science. 

In his interview with Naukri Learning, Mr. Deep talks about what he is working on now at dunnhumby, what does a day in the life of a data science manager look like, and what types of career opportunities are available for a data scientist. 

He also shares some lessons that he has learned to excel in the field of Data Science.

Let’s start a conversation with Mr. Deep Sachdev.

Interview Log – Mr. Deep Sachdev

Naukri Learning – Please share a brief introduction about your role as a data scientist.

Deep – I lead a team of data scientists to solve complex business problems in the world of retail and deliver compelling actionable insights using the best science to our clients.

As a data science manager, I spend a lot of time with the data scientists in my team to help them deliver data science projects helping our retail clients in the area of Category Management, Pricing and Promotions, Customer Knowledge, and Customer Engagement by deploying the best algorithms in an efficient way.

I closely work with client leads to develop an annual client work plan tailored to their business needs and strategy.

As a data science manager, I am also responsible for hiring, mentoring, motivating, and retaining a high-performing team of data scientists who can deliver value to the clients adopting global best practices.

Naukri Learning – What types of career opportunities are available for a data scientist? Could you please share some insights?

Deep – Data science is a multidisciplinary field with a lot of options for people from different backgrounds. Depending on the interests and skills,  one can choose to specialize as a Data Scientist, Data Architect, Data Engineer, ML Engineer, Statistician, Data Visualization Specialist, etc as their career options.

At dunnhumby, we offer broadly 3 types of career paths in data science- Applied Data Scientists, Research Data Scientists, and Data Science Engineers.

Naukri Learning – Which are the top companies in this field?

Deep – It would be unfair to take just a few names as almost every company now realizes the importance of data and the value they can unlock using data science. However, major technology companies like FAANG (Facebook, Apple, Amazon, Netflix, and Google), unicorns like Uber & Zomato, and data science specialist companies like dunnhumby, Fractal, Mu Sigma are some of the top names. Even all the IT giants now have a separate data science vertical in their organization.

Just to give you some perspective, dunnhumby India office itself has close to 300 data science professionals which makes it the engine for the growth of the company.

Naukri Learning – What would you say is your motivation behind pursuing a fair niche field?

Deep – I would say it was a niche field a few years back when I started or maybe even before that, but since then it has gained immense popularity and it has now become a preferred career choice not just for fresh talent but also for professionals from other domains.

My biggest motivation comes from the fact that data science is very entrepreneurial in nature. 

It gives you a lot of opportunities to experiment and express yourself as the same problem can be solved in multiple ways, but you should know which one to pick.

It requires not only good technical skills like coding, data mining, and ML algorithms, but you have to be good at storytelling and communication skills, people and client management skills, etc.

Naukri Learning – Tell us about some lessons that you have learned to excel in this field. 

Deep – Don’t assume things. Many times even the client wouldn’t have a clear idea of what they want, so develop good listening skills and try to translate the business problem into an analytical problem in the most simple manner.  We at times are very excited to deploy cutting-edge algorithms but there are a lot of cases where a sledgehammer is not required for peanuts.

Naukri Learning – What does a day in the life of a data scientist look like?

Deep – A data scientist will be at the centre of many things as they have to –

  • Participate in client meetings, as required, to present methodology and solutions through effective storytelling techniques and help influence client decision making. 
  • Work with data engineers to understand the data available and do data wrangling to make it ready for the analysis.
  • Write codes using R, Python, Spark and use tools like Gitlab for code collaboration
  • Work with the products team to provide feedback on enhancing the current product offerings, explore new solutions that can potentially become a product.

Naukri Learning – What skills or characteristics make someone an effective remote worker?

Deep – One needs to manage time effectively and should possess excellent verbal and written communication skills as you would be required to connect with a lot of people virtually.

Collaboration is an important aspect of remote working as you are physically not present amongst your peers so one should be able to put conscious efforts to collaborate with others effectively.

Naukri Learning – Any courses/paths that you’ll recommend to aspiring data scientists?

Deep – With platforms like Udemy, Coursera, and many others, aspirants are spoiled with choices as far as the availability of resources is concerned. Like I said earlier, it’s a multidisciplinary field and offers a lot of options. But data remains at the core of everything so as a starting point I would suggest one should know how to play with data using any of the most popular open-source languages like R & Python.

Naukri Learning – Last words – Do you have any expert advice for our readers? 

Deep – Data science is very vast and evolving at a pace like never before, so there will always be something new to learn. So it’s completely OK not to know everything as long as you are prioritizing what you want to learn and become an expert at it. 

 

Disclaimer: The views, suggestions, and opinions expressed here are those of the expert.

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