DGM / GM / Sr. GM - Data Scientist / Bangalore Location

BVR People Consulting; Bengaluru; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

BVR People Consulting in Bengaluru, India, seeks a Data Scientist Generative AI & Machine Learning to design, develop, evaluate, and deploy AI solutions for real-world business problems. You will combine classical ML, statistical modeling, Python data science, and GenAI/LLMs to build production-ready solutions, collaborating with engineering and MLOps teams.

The ideal candidate has 6–9 years of experience in engineering/AI analytics and a strong background in Python, ML, statistics, and GenAI

Qualifications

• 6 to 9 years of hands-on data science experience.
• Strong background in Python, ML fundamentals, and statistical modeling.
• Experience building production-ready GenAI/LLM solutions and RAG workflows.

Responsibilities

• Translate business problems into Data Science and AI solutions.
• Build, train, tune, and evaluate ML models for various tasks.
• Develop GenAI/LLM initiatives including retrieval augmented generation.
• Collaborate with Engineering and Product teams to productionize solutions.
• Design evaluation frameworks for model quality, bias, and robustness.

Skills

Python

Statistics

Data Analysis

GenAI

LLMs

Prompt Engineering

MLOps

LangChain

LangGraph

Education

Bachelor's or Master's in Computer Science, Data Science, Statistics, AI, ML

Tools

LangChain

LangGraph

MLOps

Job description

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 strong 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: 6 to 9 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

Thanks & Regards,

Gowsalya