Data Scientist

Birlasoft · IT Consulting & Digital Transformation · Enterprise Apps Implementation Partners · Python · SQL · 8 days ago
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Salary
≈ $18k – $49k per year (Estimated)
Location
In office (Bengaluru)

Confirmed on the employer's own hiring board on Oct 28, 2026. First seen by Alion on Oct 22, 2026. Birlasoft scores A on the Alion truth index.

Overview
Company
Impact
Profile match

Birlasoft

Birlasoft is an Indian IT services company, part of the CK Birla Group, that provides enterprise application implementation, cloud migration, digital engineering and data services. It works with SAP, Oracle, Salesforce and Microsoft platforms for manufacturing, life sciences, energy, utilities and financial services clients in North America, Europe and Asia. Its openings are largely for Salesforce developers and CPQ specialists in Pune, Bengaluru, Hyderabad and Noida. The company is headquartered in Noida, Uttar Pradesh, India.
birlasoft.com · HQ: Noida, India · Cloud Consulting & Migration · IT Consulting & Digital Transformation · Enterprise Apps Implementation Partners · 1001-5000 employees · Est. 1990
Tech stack of Birlasoft

Area(s) of responsibility

5A Grade

Key Responsibilities

- Design and implement GenAI and Agentic AI solutions using Databricks Genie, Databricks Agent Bricks, Mosaic AI (model training, evaluation, prompt engineering, RAG)

- Experience Build LLM-powered use cases

- Design and build scalable data pipelines using Databricks, PySpark, and SQL

- Implement Delta Lake, Unity Catalog, and medallion architecture

- Optimize Spark jobs for performance, cost, and scalability

- Perform data ingestion, transformation, and enrichment from multiple sources

- Ensure data quality, reliability, and observability across pipelines

- Design and develop enterprise ontologies, taxonomies, vocabularies, and semantic data models.

- Support AI/ML workloads by preparing high-quality, feature-ready datasets

- Develop and fine-tune LLMs/ML models using Databricks MLflow and Mosaic AI

- Implement prompt engineering, model evaluation, and guardrails for enterprise GenAI use cases

- Integrate AI solutions with enterprise data and business workflows

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