Browse Jobs
Explore open roles across India.Explore active software roles. Sign up to apply and get AI match scores.
Top MatchesTop Job Matches
Loading jobs…
Back to Browse Jobs
Tredence
Lead Data Scientist - Classical ML / Gen AI
Tredence
Pune•Hybrid•5-8 Yrs•1 hour ago
Job description
Hybrid
Overview
You are an experienced Lead Data Scientist or Lead GenAI Developer who will be joining the India team either in Bengaluru, Gurugram, Hyderabad, Pune, or in a remote/hybrid setup.
Responsibilities
- Lead development of demand forecasting models using time series (ARIMA, Prophet, TFT) and ML (XGBoost, LightGBM).
- Design and deploy price elasticity models and dynamic pricing optimization using econometric methods, causal inference, and bandits.
- Build inventory/revenue optimization engines using linear programming, heuristics, or reinforcement learning.
- Own the end-to-end model lifecycle including feature engineering, backtesting, deployment, monitoring, and retraining.
- Mentor a team of 36 data scientists and ML engineers.
- Architect and deploy RAG pipelines for enterprise knowledge retrieval using vector DBs like Pinecone, FAISS, Weaviate, and embeddings.
- Design autonomous agentic systems with frameworks like LangGraph, CrewAI, or AutoGen for multi-agent orchestration, tool use, and memory.
- Fine-tune LLMs (OpenAI, Llama, Mistral) for domain-specific tasks, implement prompt engineering and evaluation (RAGAS, DeepEval).
- Deploy GenAI solutions on cloud platforms with latency/cost optimization in AWS Bedrock, Azure OpenAI, or GCP Vertex AI.
- Lead a team of GenAI developers and prompt engineers.
- Lead development of demand forecasting models using time series (ARIMA, Prophet, TFT) and ML (XGBoost, LightGBM).
- Design and deploy price elasticity models and dynamic pricing optimization using econometric methods, causal inference, and bandits.
- Build inventory/revenue optimization engines using linear programming, heuristics, or reinforcement learning.
- Own the end-to-end model lifecycle including feature engineering, backtesting, deployment, monitoring, and retraining.
- Mentor a team of 36 data scientists and ML engineers.
Qualifications
- 812 years in Data Science/ML with at least 2+ years in a lead role.
- Deep expertise in forecasting, price elasticity, and optimization.
- Proficiency in Python, SQL, and experience with scikit-learn, PyTorch/TensorFlow, statsmodels, Prophet, or OR-Tools.
- Strong cloud deployment experience in AWS SageMaker, Azure ML, or GCP Vertex AI.
- Bachelors degree in CS/Stats/OR/Economics; Masters or PhD preferred.
- *GenAI / RAG / LLM / Agentic**
- 812 years in AI/ML development with a focus on Generative AI and agents for at least 2+ years.
- Strong experience in RAG, LLM orchestration, and agentic workflows.
- Proficiency in Python, LangChain/LangGraph, vector databases, and LLM APIs.
- Cloud deployment expertise in AWS Bedrock/SageMaker, Azure AI Foundry, or GCP Vertex AI with MLOps/LLMOps practices.
- Bachelors degree in CS/AI; Masters or PhD preferred.
- *Common Requirements:**
- 812 years of relevant experience.
- Hands-on experience deploying models/agents to production on cloud, preferably with Docker, Kubernetes, CI/CD pipelines.
- Strong stakeholder management skills and the ability to translate business problems into technical solutions.
- Excellent communication skills in English to collaborate with India-based and global teams.
- Published research or contributions to open-source AI/ML projects.
- *Classical ML / Forecasting / Pricing**
- 812 years in Data Science/ML with at least 2+ years in a lead role.
- Deep expertise in forecasting, price elasticity, and optimization.
- Proficiency in Python, SQL, and experience with scikit-learn, PyTorch/TensorFlow, statsmodels, Prophet, or OR-Tools.
- Strong cloud deployment experience in AWS SageMaker, Azure ML, or GCP Vertex AI.
- Bachelors d