A role with Data Science and Analytics (DSA) means being a part of the team that works closely with the business and identifies problems / opportunities for improved decision-making through better data analysis. This covers the whole gamut from simple descriptive analysis to more complex predictive and prescriptive analytics, using advanced modeling and machine learning techniques primarily using open source technologies and big data platforms. The emphasis is on actionable insights, which is possible through a combination of technical skills and business understanding.
As Data Analyst, DSA you will work closely with business/product teams and understand their priorities/roadmap. Based on this understanding, you are expected to identify appropriate metrics that will drive the right decisions for the business, and then build reporting solutions to deliver these metrics at the required frequency in an optimal and reliable fashion. You will also answer ad-hoc questions from your business users by conducting quick analysis on relevant data, identify trends and correlations, and form hypotheses to explain the observations. Some of these will lead to bigger analytical projects of increasing complexity, where you will work initially as a part of a bigger team, but also work independently as you gain more experience. Finally, you are expected to always adhere to project schedule and technical rigor as well as requirements for documentation, code versioning, etc.
Core responsibilities are described within this job description. Job duties may change at any time due to business needs.
- B.Tech / B.E. or Masters in Statistics /Econometrics/Mathematics equivalent
- Strong SQL or PL/SQL programming skills
- Big data experience
- Exposure to R, Python, Hive, or other open source languages
- Understanding of foundational mathematics and statistics
- Conceptual understanding of analytical techniques like Linear Regression, Logistic Regression, Time-series models, Classification Techniques, etc.
- Strong written and verbal communication skills to explain complex analytical methodologies to clients regardless of the clients technical expertise
- “Hands-on” experience in analytics / data science preferable
- Any experience with Retail, Merchandising, Marketing will be strong addons