Data Scientist
MAN TRUCK & BUS INDIA PVT. LTD
Pune District, Maharashtra, India4h agovia LinkedIn
About the Role
This is a permanent position located in Pune (Hybrid working policy).
Key Responsibilities
- Data Modelling & Analytics:
- Strong Python and SQL for data extraction, transformation, analysis, modelling, validation and insight generation from large datasets.
- Knowledge of Machine Learning methods including clustering, decision trees, artificial neural networks and related approaches.
- Solid understanding of statistical methods including regression, statistical distributions, hypothesis testing and model evaluation.
- Strong understanding of data-quality methods, validation checks, transformation logic and reliable metric definition.
- Experience delivering vibe-coded PoCs to business units for initial feedback.
- AI & Advanced Analytics:
- Experience with GenAI-assisted workflows such as n8n or UiPath.
- Experience with comparison logic, review workflows and quality-evaluation methods for AI-generated outputs.
- AWS/AI:
- Experience delivering AI use cases on AWS using S3, Glue, Athena, Lambda and Bedrock.
- Coding Assistants:
- Extensive experience using coding assistants such as AWS Kiro, GitHub Copilot, OpenAI Codex and Claude Code.
- Business Collaboration:
- Ability to translate business needs into analytical use cases, data requirements, implementation tasks and measurable outcomes.
- Communication:
- Good communication skills and ability to clearly explain data models, analytical methods, technical constraints, validation results and business value to technical and non-technical stakeholders.
Requirements & Tech Stack
- Python
- SQL
- Machine Learning
- Statistics
- Data Analytics
- Data Quality
- Validation
- Metrics
- PoC Development
- GenAI
- n8n
- UiPath
- AWS S3
- AWS Glue
- AWS Athena
- AWS Lambda
- AWS Bedrock
- AWS Kiro
- GitHub Copilot
- OpenAI Codex
- Claude Code
Qualifications
- Experience in Data Science, Data Analytics, or data-driven software quality use cases.
- Experience translating business questions into analytical concepts, data requirements, implementation tasks, and acceptance criteria.
- Good to Have: Domain experience with automotive, software quality, defect analysis, issue tracking, test case, or engineering data.