Hi,

Warm Greetings!

We are looking for an experienced Data Scientist Generative AI & Machine Learning to design, develop, evaluate, and deploy AI solutions for real-world business problems. The role requires a solid combination of Classical Machine Learning, Statistical Modeling, Python-based Data Science, and Generative AI/LLM technologies. The ideal candidate should have hands-on experience in building production-ready ML and GenAI solutions, working with engineering/MLOps teams, and translating complex business problems into scalable AI solutions.

Experience: 69 Years

Industry: Engineering / Technology / AI & Analytics

Key Responsibilities

- Translate business requirements into Data Science and AI problem statements and define appropriate solution approaches.
- Perform EDA, data analysis, feature engineering, preprocessing, and statistical analysis.
- Build, train, tune, and evaluate Machine Learning models for regression, classification, forecasting, clustering, segmentation, and anomaly detection.
- Develop Generative AI and LLM-based solutions for knowledge assistance, Q&A;, summarization, extraction, reasoning, and decision support.
- Design and implement RAG (Retrieval-Augmented Generation) workflows including document processing, embeddings, retrieval, and response generation.
- Perform Prompt Engineering, testing, and optimization of LLM-based solutions.
- Contribute to Agentic AI / AI agent solution design from a reasoning and orchestration perspective.
- Develop evaluation frameworks to assess ML model performance, GenAI quality, hallucination, bias, robustness, and consistency.
- Collaborate with Engineering, MLOps, and Product teams to move solutions from experimentation to production.




- Support model monitoring, retraining, documentation, lifecycle management, and continuous improvement.
- Build reusable ML/AI components, solution templates, and best practices.

Required Skills Programming & Data Science

- Strong hands-on experience in Python
- NumPy, Pandas
- Strong understanding of statistics and data analysis

Classical Machine Learning

- Scikit-learn
- XGBoost / LightGBM
- Regression and Classification
- Time Series Forecasting
- Clustering and Segmentation
- Anomaly Detection
- Feature Engineering and Model Tuning
- Model Evaluation and Validation

Generative AI

- Hands-on experience with LLMs
- Generative AI application development
- Prompt Engineering
- RAG / Retrieval-Augmented Generation
- LangChain / LangGraph
- Understanding of LLM strengths, limitations, and hallucination management
- Exposure to Agentic AI / AI orchestration is an advantage

Production & Collaboration

- Experience delivering end-to-end AI/ML solutions
- Exposure to MLOps / model deployment / monitoring
- Experience working with Engineering and Product teams
- Strong analytical, problem-solving, and communication skills
- Ability to explain technical concepts to non-technical stakeholders

Preferred Qualifications

- Experience in enterprise-scale AI/ML projects
- Experience with Responsible AI, explainability, fairness, and model validation
- Experience mentoring junior Data Scientists
- Exposure to cloud platforms such as AWS, Azure, or GCP
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Artificial Intelligence, Machine Learning, or a related quantitative/technical field

If you are interested, please share your cv to [email protected] Thanks & Regards,

Gowsalya

📌 DGM / GM / Sr. GM - Data Scientist / Bangalore Location (Bengaluru)
🏢 BVR People Consulting
📍 Bengaluru