Uber off-campus recruitment drive to hire candidates for  Data Science Intern. Interested candidates can read the details and apply as soon as possible.

About: Uber Technologies commonly known as Uber, is an American technology company. Its services include ride-hailing, food delivery (Uber Eats), package delivery, couriers, freight transportation, and, through a partnership with Lime, electric bicycle and motorized scooter rental. The company is based in San Francisco and has operations in over 900 metropolitan areas worldwide. It is one of the largest firms in the gig economy.

Position: Data Science Intern

Location: Bangalore

Experience: Freshers

Qualification: M.E/M.Tech


  • Current M.Tech student majoring in Computer Science, Economics, Statistics, Machine Learning, Operations Research, or other quantitative fields.
  • Anticipated graduation in 2023.
  • Familiarity with underlying mathematical foundations of statistics, machine learning, optimization, economics, and analytics.
  • Experience with exploratory data analysis.
  • Proficiency in languages like SQL, R, and Python.
  • Experience with exploratory statistical analysis, testing, and model development.
  • Ability to communicate effectively with both technical and business partners.
  • Experience in experimental design and analysis (e.g., A/B and market-level experiments), as well as causal inference.
  • Independence, excellent communication, and outstanding follow-through – you energetically tackle your work and love the responsibility of being individually empowered.

Job Responsibilities: 

  • Work with your mentor closely to scope a project, define the problem, and develop and prototype the solution using data-driven approaches.
  • Work with engineers and product managers to turn data science prototypes into robust, reliable solutions.
  • Present findings to business leaders to inform decisions.
  • Establish standard methodologies for data science including modeling, coding, analytics, optimization, and experimentation.
  • Conduct experiments to advise product decisions.


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