Deputy Manager - Data Scientist

About ReNew Power

Established in 2011, ReNew Power is a leading renewable energy firm with a dominant presence in India and global reach. Listed on Nasdaq as RNW, ReNew focuses on developing and managing utility-scale wind and solar power projects, along with firm power and distributed solar energy solutions. With over 13.4 GW capacity across 150+ sites in 18 Indian states, the company contributes significantly to India’s power supply and carbon emissions reduction efforts. ReNew aims to serve as an integrated decarbonization partner by leveraging clean energy, green hydrogen, digital solutions, energy storage, and carbon markets to combat climate change. They have created approximately 130,000 direct and indirect jobs and count several premier investors among their shareholders. The company is devoted to delivering sustainable, affordable, and safe energy while leading climate action in India.

Role Overview

ReNew Power is looking for a Data Science and AI Engineer with 6 to 8 years of experience, preferably holding a Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related disciplines. The candidate should have a strong foundation in data science techniques, particularly predictive analytics and forecasting, combined with practical experience deploying production-grade Generative AI (GenAI) systems. The role is based in Gurugram.

Key Responsibilities

• Architect and create scalable Generative AI applications such as copilots and chatbots.
• Design and enhance Retrieval Augmented Generation (RAG) pipelines for AI workflows.
• Develop agentic workflows employing frameworks like LangGraph or LangChain.
• Utilize forecasting and predictive modeling skills for renewable energy use cases including generation, price, demand forecasting, and asset performance prediction.
• Build RESTful APIs and AI microservices using FastAPI or equivalent tools.
• Implement observability and monitoring systems leveraging OpenTelemetry, LangSmith, Grafana, or similar platforms.
• Optimize AI solutions for performance parameters including latency, scalability, reliability, and operational cost.
• Collaborate with multi-disciplinary teams to deploy AI and data science solutions into production environments.

Mandatory Technical Expertise

• Experience delivering and managing at least one live production GenAI project, specifically involving RAG-based chatbots, copilots, or AI assistants serving real user traffic, with understanding of operational challenges like latency, cost management, scaling, failure handling, monitoring, and continuous improvement.
• Hands-on expertise in predictive modeling and forecasting using time-series analysis, regression, ensemble methods like LightGBM or XGBoost, and deep learning architectures.
• Strong capabilities in statistical modeling, feature engineering, and evaluation techniques for forecasting problems.
• Practical knowledge of LangGraph, LangChain, or similar orchestration tools for AI workflows.
• Thorough understanding of RAG architectures including embeddings, chunking methods, retrieval tuning, and vector search techniques.
• Proficient Python programming skills.
• Experience developing REST APIs with FastAPI.
• Familiarity with vector databases/search tools such as Azure AI Search, Pinecone, Milvus, or FAISS.
• Experience with monitoring and observability tools including OpenTelemetry, LangSmith, Langfuse, Grafana, or Azure Monitor.
• Knowledge of cloud platforms like Microsoft Azure, AWS, or Google Cloud Platform.

Desirable Skills

• Prior exposure to energy, utilities, or manufacturing sectors with forecasting focus (demand, price, generation, or maintenance).
• Experience handling semantic caching, query rewriting, or guardrails in live RAG systems.
• Working knowledge of multimodal AI systems.
• Familiarity with containerization and orchestration technologies such as Docker, Kubernetes, along with CI/CD pipeline experience.
• Understanding of AI safety principles, guardrails, and prompt engineering.

Eligibility Criteria

• Strong aptitude for system design and advanced problem-solving.
• Ability to integrate classical machine learning rigour with contemporary Generative AI system designs.
• Effective communication and teamwork skills.
• Capability to present architectural insights and lessons learned from deployed RAG/chatbot systems during interviews.

Competencies

• Change Management
• Data Analytics and Reporting
• Effective Communication
• Information Systems Management
• Problem Solving
• Process Planning
• Project Management
• Technology Acumen
• Sector Knowledge
• Strategic Thinking
• Initiative and Proactivity