Senior Data Scientist

Flipkart · Bengaluru

  • Experience3–7 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelmid
  • Posted2 Sept 2026
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About Flipkart

Flipkart is hiring in Bengaluru in ecommerce retail. This role looks for around 3+ years of experience.

Skills

  • machine learning
  • statistical models
  • Python
  • R
  • regression
  • clustering
  • neural networks

The role

A data scientist at an e-commerce marketplace develops machine learning and statistical models for business and product problems, uncovering insights through regression, clustering, and neural networks. The role applies Python and R to research-driven solutions and collaborates with product stakeholders.

Full job description

A Data Scientist at Flipkart is required to develop and implement ML or statistical models for the various projects formulated from business and product views. The responsible person should be able to communicate and collaborate with multiple stakeholders representing various teams to better understand the problem at hand. At a fundamental level, the responsible person should be able to dive deep into a problem statement and extract interesting insights as well as solutions. In addition to being a quick learner, a DS is expected to get involved in active research projects with a view to publishing them.

Responsibilities:

Understand business and product needs and use ML or statistical techniques to provide solutions to those in a time-bound fashion.

Communicate and collaborate with business and product teams to have a better understanding of the project so as to be able to drive it within the DS team.

Get involved in an in-depth exploration of solutions using various methods and extract statistical insights from data as well as models, which are to be shared with business and product teams.

Active participation in working with new methods and learning new technologies, both in the areas of data science and data engineering.

Requirements:

B. Tech or M. Tech in CS or Statistics with experience ranging from 5 to 12 years through publications/deployed solutions/projects.

Deep understanding of the algorithms (theory and application) that they have worked on.

Good grasp on the theory and practice of basic statistical models such as regression or clustering and general ML algorithms such as trees, random forests, SVM, boosting, neural networks, etc.

It is not expected that the candidate has actually worked on all these modules.

Strong proficiency in Python or R is necessary.