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Data Scientist - Face To Face interview -Immediate-Bengaluru

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Onsite

Data Scientist - Face To Face interview -Immediate-Bengaluru

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Data Scientist - Face To Face interview -Immediate-Bengaluru

Skills

Google Cloud PlatformSQL QueriesDockerPythonDesign ThinkingMachine LearningAWSNLP / Natural Language ProcessingPySparkAzure

1 month ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

23 September 2026

What they need


Job Title: Data Scientist (2.5 Years -4.5 Years )

Job Loc: 77 Town Center, 3, Yemalur, Bengaluru, Karnataka

Mode of Work: 5 days work from office)

Interview Process (F2F Involved):

  • Round : FacetoFace (F2F) Interview

Job Role:

  • Investigate the feasibility of applying scientific principles and concepts to business problems.
  • Develop new algorithms independently to solve well defined retail problems and improve existing algorithms.
  • Work with product team to implement new modules, maintain and release production pipelinesin timely and responsible manner.
  • Develop POCs based on new ideas or technology, popularize new innovations in retail andanalytics with internal/external stakeholders.
  • Collaborate with Data Engineering, Advisory and Product team to find scope of improvementand drive right processes.

Who are we looking for?

  • Writes efficient code inPySpark or Python (At least 3+ years):
  • Experience in writing production system code (Modular code build, OOP framework, test cases,exception handling etc.)
  • Efficient data processing (vectorization, avoiding row-wise ops etc.)
  • Rudimentary knowledge of asymptotic algorithm analysis
  • Fluency in SQL, relational database, and non-structured data handling**(Images, text blob)**
  • In-depth knowledge in machine learning with mathematical foundation for any two of thefollowing modelling techniques:
  • Regression (classical; DL is a plus)
  • Classification (classical & DL)
  • Text Mining/ NLP
  • Recommender Systems

Good to Have:

  • Exposure to GenAI systems (LLMs, RAG, or agentic workflows) and interest in designing beyondbasic use case (Situational and case-basis design thinking)
  • Exposure in cloud technology and model deployment (Azure/ AWS/ GCP)  theoreticalbackground with foundational concepts of docker, CI-CD etc., works.
  • Retail Experience & Business Acumen (Even if its 30-50% of overall experience – at least one retail project)

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