Data Scientist
₹2,000,000 – ₹3,000,000 / yr base salary
Posted 14 Oct 2026
Advertised as “Senior Data Scientist”
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- People management
- Contract
- Full-time
| Base salary | ₹2,000,000 – ₹3,000,000 / yr |
|---|
Field of studyComputer Science, Engineering (or related)
Study levelBachelor's or higher
𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀
𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟮𝟬𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟯𝟬𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟮𝟬-𝟯𝟬 𝗟𝗣𝗔)
Experience: 5+ yrs
Location: Bengaluru, Chennai
Job Type: Full-time
We are looking for an experienced Senior Data Scientist with strong expertise in Python, Machine Learning, Generative AI, Large Language Models (LLMs), and AI engineering to develop intelligent, scalable, and data-driven solutions. The ideal candidate will combine statistical expertise and analytical thinking with practical experience building AI applications, retrieval-augmented generation (RAG) pipelines, AI agents, and production-ready machine learning systems.
You will work on complex business challenges, translating data and analytical requirements into innovative solutions that improve decision-making, automate workflows, and deliver measurable business value.
Requirements
Key Responsibilities
- Translate business challenges into analytical problems and deliver actionable, data-driven recommendations.
- Collect, process, cleanse, and validate data to ensure accuracy, consistency, and analytical reliability.
- Develop and optimise machine learning models, classifiers, predictive systems, and automation solutions.
- Build AI-powered applications, including chatbots, RAG pipelines, workflow agents, and multi-agent systems.
- Develop Python-based APIs and microservices integrating LLMs from OpenAI, Anthropic, AWS, Azure, and Google Cloud.
- Design retrieval, embedding, inference, and knowledge-processing pipelines using vector databases and knowledge graphs.
- Implement AI and machine learning workloads on AWS, Azure, and GCP using scalable cloud architectures.
- Establish deployment, evaluation, monitoring, and retraining pipelines for production AI systems.
- Apply infrastructure-as-code practices using tools such as Terraform and CloudFormation.
- Develop automated anomaly detection systems, dashboards, and reporting solutions for continuous monitoring.
- Conduct statistical analysis, hypothesis testing, experimentation, and exploratory data analysis.
- Present findings, model outcomes, and recommendations clearly to clients and business stakeholders.
- Ensure AI solutions follow appropriate security, governance, reliability, and responsible AI practices.
- Participate in architecture discussions and code reviews while maintaining clean, maintainable code.