Data Scientist_DM

About Company

Job Description

ReNew Power is World’s first renewable energy company to be recognized as a Lighthouse by World Economic Forum. The company has been recognized for adoption of 4 IR technologies to achieve growth that is not only profitable, but also sustainable. ReNew Digital (“ReD.) has been instrumental in this. ReD. consistently work towards development of new advance analytic, AI and machine learning models that could lead to tangible business value to the organization.

As a Senior Data Scientist, you will be responsible for providing simple and intuitive solutions to the most complex problems in renewable industry. This will involve building machine learning, deep learning and generative ai models which are coupled with contextual business knowledge. You will also use both management experience and data science expertise to lead analytics projects and mentor junior data scientists. You will be an integral part of conceptualizing, scoping and delivering complex analytics projects. You will do and oversee the development, testing and maintenance of analytical models which mimic business decisions. You will work with a world-class team of site managers, subject experts, data engineers and data scientists to build the next generation data-driven renewable company. Additionally, you will be responsible for continuously identifying opportunities to improve the ways of working and structuring within the analytics center of excellence.

Roles and Responsibilities-

Build and deploy production-grade ML pipelines for varied use cases across operations, manufacturing, supply chain, and more
Manage analytics strategy across multiple use cases
Work hands-on in designing, training, and fine-tuning models across traditional ML, deep learning, and GenAI (LLMs, diffusion models, etc.)
Collaborate with data scientists to transform exploratory notebooks into scalable, maintainable, and monitored deployments
Implement CI/CD pipelines, version control, and experiment tracking using tools like MLflow, DVC, or similar
Do shadow deployment and A/B testing of production models
Partner with data engineers to build data pipelines that support real-time or batch model inference
Ensure high availability, performance, and observability of deployed ML solutions using MLOps best practices
Conduct code reviews, performance tuning, and contribute to ML infrastructure improvements
Support the end-to-end lifecycle of ML products
Oversee and mentor large team of associate and junior-level data scientists, de-bottlenecking issues related to project execution
Contribute to knowledge sharing, reusable component development, and internal upskilling initiatives

Profile & Eligible Criteria

Bachelor's in Computer Science, Data Science, Statistics, Mathematics, or a related field. Master's degree preferred
Proven experience of 4-6 years as a Data Scientist or in a similar role, with a strong track record of delivering successful data science projects
Sound theoretical and practical knowledge of working in statistical analysis, machine learning techniques, and deep learning frameworks with solid of understanding of techniques related to regression, classification, NLP, Computer Vision, Generative AI
Experience in implementing and productionizing Generative AI applications using LLMs (e.g., OpenAI, HuggingFace, LangChain, RAG architectures)
Strong programming skills in Python; familiarity with ML libraries such as scikit-learn, TensorFlow, PyTorch
Hands-on experience with tools like MLflow, Docker, Kubernetes, FastAPI/Flask, Airflow, Git, and cloud platforms (Azure/AWS)
Proficiency in Python is a must. Proficiency in SQL/ spark for data manipulation is a plus
Worked in developing analytics solutions in 3-4 domains
Excellent communication skills to effectively manage a team and collaborate with stakeholders in cross-functional teams