onsite
Data Scientist / ML Engineer - Amerit Consulting
Data Scientist
Lead end‑to‑end data science projects for a renewable energy utility, building scalable ML models on AWS, extracting insights from large datasets, and collaborating with cross‑functional teams in a hybrid environment.
About the role
Key Responsibilities
- Design, develop, and deploy production‑grade machine learning models to optimize renewable energy production and grid operations.
- Extract, transform, and load (ETL) large volumes of sensor and operational data using SQL and Python.
- Collaborate with data engineers and domain experts to build data pipelines and feature stores on AWS services (S3, Redshift, SageMaker).
- Perform exploratory data analysis, feature engineering, and model validation to ensure high predictive performance.
- Document model logic, performance metrics, and deployment procedures for internal stakeholders.
Requirements
- 3+ years of experience in data science or ML engineering roles.
- Proficiency in Python, SQL, and experience with AWS ML services (SageMaker, Glue, Lambda).
- Strong background in supervised/unsupervised learning, time‑series analysis, and model deployment.
- Excellent communication skills and ability to work collaboratively in a hybrid setting.
- U.S. work authorization required; no sponsorship.
Skills
pythonmachine learningawssql