onsite
Lead Data Scientist - Energy Domain
Data Scientist
Lead data science initiatives in the energy sector, designing and deploying Azure Machine Learning pipelines, ensuring data quality, and building advanced feature engineering solutions on Databricks.
About the role
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.
Skills
azuredatabrickspython