How to Ace in the Field of Analytics?

Reelina Sircar is an Analytics professional with more than 8 yrs of Experience in Data Science and Decision Analytics. She has been focused on Data driven problems, Designed Solutions, Implemented BI Solutions. She worked across several verticals like Retail, FMCG, Healthcare, IT, Banking etc and dealt with clients from Offshore and Onsite.

1. How did you decide to be in the Field of Analytics?
   I come from the educational background involving Statistics and Mathematics. I started my job as a Business Analyst and started developing my interest in analytics domain.The interest towards analytics grew over the years as I kept gaining experience and exposure. I found myself to be a great fit in the companies I have worked with. My interests, research forte and my job role aligned and that’s how I have been in this field.
2. What do you think are the Challenges while hiring an Entry Level Talent?
   The Entry Level Talent may not have the exposure to all the Tools and Technologies. Most of them do not get an opportunity to begin with. Even if they have the opportunity, they may not be sure about their goals and milestones; they often do not get that space to have a prominent understanding of their career path and interests.
3. What are the Technical Skills required for a Data Scientist?
   According to me minimum levels of technology required for a Data Scientist are SAS, SQL, R, Python, Unix, Tableau, Excel (advanced) etc.
4. What is your Expectation from the talent pool?
   The candidates should keep up showing enthusiasm and urge to work and learn new things. There is no fear to fail as if they do not make mistakes, they will never learn. They should be comfortable in working in all grounds. If they have knowledge about basic tools and technologies, they should push themselves to learn the advanced level. As an Analyst, they should be able to understand the data, comprehend it and make sure they cover all the aspects of the solution before calling it a result. They must be able to know the concepts and what are they doing so that while interacting with clients they should be able to make them understand in layman’s language avoiding unnecessary jargon. One can always delve deeper in to the ideas of what is the concept of Artificial Intelligence or different types of Machine Learning Algorithm before starting implementing it. They should understand the purpose behind every work and business problem at hand. We look for people having good conceptual background, inquisitiveness to learn and positive attitude.