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Data Analyst

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Onsite

Data Analyst

Birlasoft

Data Analyst

Skills

SQL QueriesMongoDBDeep LearningDockerPythonData ScienceRDatabricksMachine LearningAIElasticsearchNLP / Natural Language ProcessingAzure

2 months ago

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Important information


Location:

Maharashtra, India

Work mode:

Onsite

Published on:

17 August 2026

What they need


Country/Region: IN

Requisition ID: 38199

Work Model:

Position Type:

Salary Range:

Location: INDIA - PUNE - BIRLASOFT OFFICE - HINJAWADI

Title: Data Analyst

Description:

Area(s) of responsibility

Job Description: Data Scientist Level-1 (4B)

Candidate with hands-on real-world project experience. Possessing sound fundamentals rather than surface application of techniques. Ability to learn and adapt to the ever-evolving AI field with its new techniques and technology.

Experience: 3-4 years „ 4B

Education: STEM field. B.Tech/B.E. /Masters in Computer Engineering or related fields

Work/Problem space:

  • Work will span domains – ranging from manufacturing, life-sciences, finance to retail.
  • Problems could span business functions - ranging from Operations, Sales, Finance, IT to HR

Core skills:

  • Application of Machine Learning and Data Science to problems
  • Statistical ML techniques, deep-learning, computer vision and NLP
  • Testing of models
  • Model performance analysis (evidence based/statistical)
  • Post-live monitoring of solutions

Optional/preferred:

  • Application of statistical techniques
  • Assist in deploying – API creation, docker containerization

Technology space:

  • OpenSource: Python and R
  • Coding standards based on PEP8 or Google Python
  • Platforms: Azure, Databricks (preferred)
  • Database systems: Working/integration knowledge of basic SQL based RDBMS. Optional/preferred: NoSQL document based databases (ElasticSearch/MongoDB)
  • Preferred: Exposure/knowledge of deployment strategies such as API and docker containers

Additional soft skills preferred:

  • Good communication and team working skills.
  • Learning attitude
  • Work under intermittent guidance
  • Agile working environment Collaborate with team members- - architects, data engineers and deployment teams

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