Lead Data Scientist - Energy Domain

Key Responsibilities

• Architect and lead end‑to‑end machine learning solutions on Azure, leveraging Azure Machine Learning and Databricks for scalable model development.
• Define and implement data quality frameworks to ensure reliable, high‑integrity datasets for energy analytics.
• Design and execute advanced feature engineering pipelines that capture domain‑specific signals and improve model performance.
• Mentor a team of data scientists and engineers, fostering best practices in code, experimentation, and model governance.
• Collaborate with energy domain experts to translate business problems into data‑driven solutions and communicate insights to stakeholders.

Requirements

• 5+ years of hands‑on experience in data science, with a focus on Azure Machine Learning, Databricks, and large‑scale data pipelines.
• Strong proficiency in Python and its data science ecosystem (pandas, scikit‑learn, PySpark).
• Demonstrated expertise in data quality management and feature engineering for complex, domain‑specific datasets.
• Proven track record of leading technical teams and delivering production‑grade ML models in an enterprise environment.
• Excellent problem‑solving skills and ability to work cross‑functionally with domain experts and engineering teams.