Deputy Manager-Data Scientist

About Company

Founded in 2011, ReNew, is one of the largest renewable energy companies globally, with a leadership position in India. Listed on Nasdaq under the ticker RNW, ReNew develops, builds, owns, and operates utility-scale wind energy projects, utility-scale solar energy projects, utility-scale firm power projects, and distributed solar energy projects. In addition to being a major independent power producer in India, ReNew is evolving to become an end-to-end decarbonization partner providing solutions in a just and inclusive manner in the areas of clean energy, green hydrogen, value-added energy offerings through digitalisation, storage, and carbon markets that increasingly are integral to addressing climate change. With a total capacity of more than 13.4 GW (including projects in pipeline), ReNew’s solar and wind energy projects are spread across 150+ sites, with a presence spanning 18 states in India, contributing to 1.9 % of India’s power capacity. Consequently, this has helped to avoid 0.5% of India’s total carbon emissions and 1.1% India’s total power sector emissions. In the over 10 years of its operation, ReNew has generated almost 1.3 lakh jobs, directly and indirectly. ReNew has achieved market leadership in the Indian renewable energy industry against the backdrop of the Government of India’s policies to promote growth of this sector. ReNew’s current group of stockholders contains several marquee investors including CPP Investments, Abu Dhabi Investment Authority, Goldman Sachs, GEF SACEF and JERA. Its mission is to play a pivotal role in meeting India’s growing energy needs in an efficient, sustainable, and socially responsible manner. ReNew stands committed to providing clean, safe, affordable, and sustainable energy for all and has been at the forefront of leading climate action in India.

Job Description

Role- Data Science & AI Engineer

Experience- 6 to 8 years

Location- Gurugram

Education- Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field

 

JD: Data Science & AI Engineer

We are looking for a candidate with a strong foundation in Data Science: predictive and forecasting  who has built few Generative AI systems, with at least one production-grade GenAI deployment under their belt. The ideal candidate has spent the couple of years building forecasting models, time-series pipelines, and statistical/ML systems, and has since shipped and operated a real GenAI System in production — not just a POC or hackathon build. You'll bring quantitative depth to areas like demand/price forecasting while owning GenAI architecture, observability, and agentic workflows.

 

Roles & Responsibilities

 

• Design and develop scalable GenAI applications, copilots, and chatbot systems
• Build and optimize Retrieval Augmented Generation (RAG) pipelines
• Develop agentic workflows using LangGraph/LangChain
• Apply forecasting and predictive modeling expertise to renewable energy use cases (e.g., generation forecasting, price/demand forecasting, asset performance prediction)
• Design and build APIs and AI microservices using FastAPI or similar frameworks
• Develop observability and monitoring pipelines using OpenTelemetry, LangSmith, Grafana, or similar tools
• Optimize AI systems for latency, scalability, reliability, and cost
• Collaborate with cross-functional teams to deploy production-grade AI and DS solutions

 

Technical Skills

 

Must Have:

 

• At least 1-2 production-grade GenAI projects shipped and operated live — specifically a RAG-based chatbot, copilot, or assistant serving real users/traffic (not a prototype). Should be able to speak to real production concerns: latency, cost, scale, failure modes, monitoring, and iteration post-launch
• Strong hands-on experience in predictive/forecasting data science — time-series modeling, regression, ensemble methods (e.g., LightGBM, XGBoost), or deep learning forecasting architectures
• Solid grounding in statistical modeling, feature engineering, and model evaluation for forecasting problems
• Hands-on experience with LangGraph, LangChain, or similar orchestration frameworks
• Strong understanding of RAG architecture — embeddings, chunking strategies, retrieval tuning, and vector search
• Strong Python programming skills
• Experience building REST APIs using FastAPI
• Hands-on experience with vector databases/search platforms such as Azure AI Search, Pinecone, Milvus, or FAISS
• Experience with observability tools like OpenTelemetry, LangSmith, Langfuse, Grafana, or Azure Monitor
• Familiarity with cloud platforms such as Azure, AWS, or GCP

 

Good to Have:

 

• Prior experience in energy/utilities/manufacturing domains involving forecasting (demand, price, generation, or maintenance)
• Experience with semantic caching, guardrails, or query rewriting in production RAG systems
• Experience with multimodal AI systems
• Exposure to Docker, Kubernetes, and CI/CD pipelines
• Knowledge of AI safety, guardrails, and prompt engineering

 

Eligibility Criteria

 

• Strong system design and problem-solving skills
• Ability to bridge classical ML/forecasting rigor with modern GenAI system design
• Excellent communication and collaboration abilities
• Should be able to walk through architecture and post-launch learnings of a shipped RAG/chatbot system in an interview

Competencies