As a Data Scientist in the Charging & Energy Services Analytics group, you’ll help improve the electric vehicle (EV) charging experience for both public users and commercial customers. Your work will directly support strategic decisions and engineering innovations that shape how people and businesses interact with EV infrastructure.
What You’ll Do:
- Translate complex business challenges into data-driven solutions using AI and machine learning.
- Build and maintain end-to-end data pipelines—from ingestion and cleaning to model training, evaluation, and deployment.
- Work with large-scale datasets in cloud environments (Google Cloud Platform) to develop scalable analytics products.
- Develop models for classification, anomaly detection, optimization, and generative AI (LLMs).
- Write clean, efficient Python code for data manipulation, feature engineering, and model development.
- Collaborate with cross-functional teams to identify new data sources and explore innovative analytics opportunities.
- Present insights through compelling visualizations and clear storytelling to technical and non-technical audiences.
Experience Required:
- Master’s degree (M.S.) in Data Science, Computer Science, Business Analytics, Machine Learning, Statistics, or a related quantitative field. A Ph.D. is strongly preferred, especially for candidates with deep expertise in machine learning, generative AI, or large-scale data systems.
- 3+ years of experience in AI/ML, with proven experience developing and deploying machine learning models in a production environment.
- 2+ years of experience in Google cloud platform with solutions designed and implemented at production scale
- 2+ Experience working with Airflow for scheduling and orchestration of data pipelines
- Expertise in SQL for data querying, manipulation, and database interaction.
- Solid understanding of machine learning algorithms, statistical modeling, and data analysis techniques.
- Excellent oral, written, and interpersonal communication skills.
This is a W2 contract role through Epitec, and candidates must be authorized to work in the United States. Additionally, applicants must be local to Michigan and available to work on-site or in a hybrid capacity as needed.