Data Scientist - eCommerce

We have an opportunity with one of our clients in the e-commerce domain.Please find attach JD FYR:-

Industry - E-commerce /OTT/Digital Platform is a must

5 Days Working

About the role

- We are looking for a Data Scientist to analyze large amounts of raw information to find patterns that will help improve our company. We will rely on you to build data products to extract valuable business insights. In this role, you should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine learning and research.

- Your goal will be to help our company analyze trends to make better decisions.

Job duties and responsibilities:

- Work closely with business/product team and understand their priorities/roadmap

- Build an automated and algorithmic-driven solution that will drive the right decisions for the business

- 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 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

Requirements:

- Bachelors/Masters equivalent in any Quantitative disciplines (Science, Technology, Engineering, Mathematics)

- Strong analytical thinking skills. Ability to creatively solve business problems, innovating new approaches where required

- Working knowledge in Python/R, SQL, Hadoop/Hive. Additional knowledge of Spark, Scala, Java desired but not mandatory

- Experience in Power BI/Tableau is a plus

- Ecommerce/ Edtech/ OTT background is a plus

- Understanding of foundational mathematics and statistical concepts

- Conceptual understanding of analytical techniques like Linear Regression, Logistic Regression, Time-series Models, Classification Techniques, etc.

- Strong team player with the ability to collaborate effectively across geographies

- Obsession with quality, operational excellence, and user experience

- Ability to convey rigorous mathematical concepts and considerations to non-experts