Target Hiring Drive 2023 For Data Analyst | Bangalore Location

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Target Hiring Drive 2023: Target is hiring data analyst for the bangalore location. B.E/B.Tech candidates with 2+ years of experience can apply for this role. required details are given below.

Company Name: Target

Role: Data Analyst

Location: Bangalore

Experience: 2+ years

Qualification: B.E/B.Tech

Batch: Any

Salary: Best in Industry

Target Hiring Drive 2023

Job Description:

  • As a Data Analyst for Digital, you will work closely with business 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.

Also Check: Estee Advisors Hiring 2023 For Data Analyst | Apply Now


  • B.Tech / B.E. or equivalent experience
  • 2 + years of relevant experience
  • “Hands-on” experience in analytics / data science
  • Intermediate SQL skills
  • Exposure to R, Python, Hive, or other open source languages preferable
  • Big data experience preferable
  • Strong written and verbal communication skills to explain complex analytical methodologies to clients regardless of the clients technical expertise
  • Experience in A/B test
  • Experience in Adobe analytics
  • Understanding of foundational mathematics and statistics
  • Conceptual understanding of analytical techniques like Linear Regression, Logistic Regression, Time-series models, Classification Techniques, etc.

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