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What sparked your interest in an offbeat, unconventional and unusual career such as statistics?

I have always been fond of mathematics in general. When I visited the faculty at Pune University, the Bachelor’s Course in Statistics looked a perfect fit for me and then after I graduated, I signed up for a Master’s in Statistics, which I completed in 2007.

What is your current role?

I’m Senior Team Lead in the Services division at Cytel, and am currently assigned to a biotech project where I provide publication support and validate manuscripts. A significant part of this role is acting as the statistician. I effectively bridge the gap between SAS programmers and the client by managing the requests and co-ordinating the work.

What has been your journey to your current role at Cytel?

I joined Cytel in 2008 as a Statistician in the software development team; my role was predominantly quality assurance, validating the statistical algorithms in Cytel software like EAST®. In 2013 I got the opportunity to work as the subject matter expert for EnForeSys. This is a user-friendly decision tool that leverages simulation methods to predict recruitment milestones with high accuracy. After 7 years I then moved into services to support a specific client project, the project ran for 18 months. This brings me to my current role where I am the Senior Team Lead. This is a customer focused position and I am learning new terminology to ensure I can interact with a technical and non-technical audience.

What are your key research interests?

It’s important to not get so involved in our routine work that we overlook a problem that’s worth exploring more deeply. I got the opportunity to work closely with Dr. Gore and Dr. Paranjpe, both principal statisticians at Cytel India, who were my professors during my Master’s degree. They encouraged us to explore such problems that we come across with no textbook solutions. Sometimes the problem may seem trivial, but it could actually be of high importance in the real world application. The poster to be presented at the WSDS 2017 conference is the outcome of one such exploration. Taking up such research work also gives me a chance to do some R programming which always excites me.

What career achievements are you most proud of?

A significant part of my career was working on an R programming assignment for a leading biopharmaceutical company for forecasting the recruitment process in clinical trials using simulations. This gave me exposure to R programming, which further gave me visibility within the organization and helped me to market my technical abilities.

Last year at PhUSE I presented a paper on ‘R Beyond Statistics’ which was about an R tool that I developed for one of our clients and I was delighted to win the best presentation in my stream. 

What most inspires you about working within this field? 

My love for mathematics as it is crucial for being a Statistician. I am lucky that I can apply my passion to my work. Working as a statistician allows me to work with data to help find practical solutions to problems. My job is always challenging and exciting, to date I have never had a mundane exercise.

Pharmaceutical companies face many challenges and very often you are involved in finding a solution to a unique problem – this is very motivating and gratifying.

What would be your three top tips for early career statisticians looking to develop in this field? 

  • Love the subject! Statistics is a field where there is no routine job, you are regularly faced with intellectual challenges and you have to think about every situation in terms of probability or variation. It is an exciting industry to be in.
  • Understand what is your area of interest, there are many fields with application of statistics, but the role of a statistician could be very different in each field. You must pick your field according to your interest and skill sets. It is important your subject knowledge is strong, it’s not just the statistics, but you have to take into account the domain and have an understanding of both.
  • You must be able to present complex statistical concepts, results and outputs in a way which clients can understand, sometimes this will be to a non-technical audience and you are required to act as the mediator from the data to the end user. This can be achieved only with strong basics of the subject.