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A Day In The Life Of: A Chief Data Scientist Who’s Also A Machine Learning Pro

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A Day In The Life Of: A Chief Data Scientist Who’s Also A Machine Learning Pro

Key takeaways

  • Data science is highly sought after, attracting many professionals from various backgrounds.
  • Rashi Gupta identified a gap between customer expectations and enterprise capabilities, leading her to establish Rezo.ai.
  • As Chief Data Scientist, Rashi focuses on product development, research, and algorithm creation at Rezo.
  • Previous roles emphasised capability development in machine learning and predictive analytics.
  • A strong foundation in mathematics and statistics is essential for success in data science.

Takeaways drafted with AI from the article text.

No doubt data science is the “Sexiest Job of the century”, and with all the perks such as the handsome paycheck, designation, reputation, many are making transitions into the data science domain. We have read articles, watched YouTube videos to see how the domain actually is but is it enough? Do we really have an idea of how a data scientist strike a balancing act in their daily lives? In order to give you all clear view and for our column ‘A Day In The Life Of’, this time we caught up with Rashi Gupta, Co-founder & Chief Data Scientist, Rezo.AI. Rashi always felt that there is a huge gap between customer expectation and how the enterprise was trying to match them. And she had some great ideas on how to bridge the gaps and thus decided to start her own venture, Rezo.ai. Today, as the Chief Data Scientist at Rezo, she handles the company’s product drafting, feature identification, R&D, and algorithm development.  Every morning when she steps inside the office, she makes sure that her team has all their questions answered so the deliverables happen smoothly. When asked about her responsibilities at Absolutdata and WNS, she said, “Both at Absolutdata and WNS, the key focus was on capability development in the area of Machine Learning, Text Analytics and Predictive Analytics along with algorithm development for their products.”

The Educational Aspect

To be data scientist, it is imperative for an individual to have a strong hand in mathematics — a solid foundation in advanced statistics. Rashi believes is important to not only be able to identify and run a pre-developed algorithm in Python or R but to be able to understand and appreciate the variables and the probable values these algorithms can take to achieve the desired results. “Unless you understand the logic/mathematics behind the algorithms, you will never be able to deploy the appropriate algorithm required for processing the data,” said Rashi As a word of advice to all the fresh graduates and to people from a non-technology background, Rashi thinks if an individual has an analytical mind, she/he can get their hands on analytics. Here are three skills that she looks at when training armatures: Keenness to look through the data, a champ in one programming language, and open to research and learn. “Data science is a difficult journey. But it is really worth taking a risk,” said Rashi.

Striking A Perfect Work-Life Balance

Rashi is a morning person — she starts her day early in the morning at 5:30 AM. She makes sure that all her work and responsibilities are wrapped before she leaves for work. “Almost everything is planned a day before, both at work and at home, so there are no surprises. We work 6 days a week and Sunday is day off,” said Rashi. Despite all the responsibilities she has in terms of work — being the co-founder and chief data scientist at Rezo, Rashi makes sure that she strikes a pretty good work-life balance. She spends her Sundays with her 7-year-old daughter. They either swim together or read a book or do a project together or watch a movie. “Striking a balance is very important. But sometimes it gets extremely difficult when both husband and wife work together. Work never ends and you find difficult to disconnect even at home,” Rashi added.

A Perfect Leader

As Rashi walked us through her day in the life, we asked her how she manages her team at work. Rashi reckons that team management is easy if each member has well-defined expectations, deliverables with timelines. “As a young company, each member has the freedom to adapt their style until the time work is being delivered with quality on time. Having said this, creating a good project plan is a tough task and that is where the experience comes handy,” said Rashi. Talking about prioritizing work, she believes that as a data scientist, it is important to know the problem at hand and a clear idea of the output expected. Once these are clear, he/she needs to draft a rough sketch of algorithms that needs to be tested along with parameterization. “All of these need clear planning, else it’s easy to get carried away and achieve absurd results,” Rashi added. When asked about the best part of her work, Rashi said it’s her team. “What I like most about my job/workplace is my team – a passionate set of data scientists and developers who work as long as it takes to deliver what we promise,” said Rashi As a fun Q, we asked Rashi what is it that makes data scientists different from other IT professionals at work, and she said, “it is the planning and time spent in problem understanding.” Quoting Abraham Lincoln "Give me six hours to chop down a tree and I will spend the first four sharpening the axe.”

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