Description

You will build and maintain large-scale data processing pipelines and machine learning solutions within a cloud-native environment.

This role is on-site.

Responsibilities

• Develop and maintain Python programs for machine learning functions and data filtering, ensuring software traceability via GitHub.
• Build and automate data products and reporting pipelines in collaboration with data scientists and analysts.
• Design and implement data management programs for SQL databases, including data selection and uploading processes.
• Analyze factory, user, and failure data to resolve battery-specific engineering problems using time series analysis.
• Organize sample sizes and key pulls from client databases to minimize SQA issues and maximize efficiency.

Required Skills

• 6+ years of experience as a data scientist, data engineer, or analyst.
• MS or Ph.D. degree in a relevant field.
• Proficiency in Python and its ecosystem, including NumPy, Pandas, TensorFlow, and PyTorch.
• Strong working knowledge of Snowflake, SQL, Airflow, DBT, and Conductor.
• Experience with large-scale data processing pipelines and cloud-native environments.
• Solid competency in statistics, algorithm design, and model building.
• Familiarity with database modeling and data warehousing principles.
• Ability to use proper metrics to evaluate machine learning model results.

Preferred Skills

• Battery engineering experience.
• Experience working in a matrix environment.

Key Skills

Education

MS or Ph.D