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Data Scientist

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Onsite

Data Scientist

Data Labs - LANDMARK GROUP

Data Scientist

Skills

SQL QueriesData EngineeringPythonDesign ThinkingData AnalysisMachine LearningNLP / Natural Language ProcessingPySpark

8 days ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

17 October 2026

What they need


About CSi (Customer, Strategy & Intelligence)

CSi is the Customer, Strategy & Intelligence division of Landmark Group Globally. It brings together the former DLL (Data Labs Landmark), the Group Loyalty function (Shukran), Partnerships, Performance Marketing, and Martech.

Job Location: 77 Town Center, 3, Yemalur, Bengaluru, Karnataka 560037

Who are we looking for?

  • Experience: 1.5 to 4.5 years
  • Writes efficient code in PySpark or Python (At least 2.5 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 the following 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 beyond basic use case (Situational and case-basis design thinking).

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 pipelines in timely and responsible manner.
  • Develop POCs based on new ideas or technology, popularize new innovations in retail and analytics with internal/external stakeholders.
  • Collaborate with Data Engineering, Advisory and Product team to find scope of improvement and drive right processes.

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