Senior Data Engineer: Anomaly Detection & Analytics

General Motors (GM); Warren (MI); Híbrido; USD 125 000 - 169 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Relocation benefits

Resumo da oferta

General Motors (GM) in Warren/Austin area seeks a Senior Data Scientist to develop and operationalize data science solutions that identify emerging vehicle, software, and product-quality issues before they become risks.

This role partners with Product Quality, Warranty, Vehicle Engineering, software teams, and others to translate complex questions into trustworthy metrics, detection algorithms, dashboards, and alerts.

Qualificações

• 7+ years of data engineering/development or related experience.
• Experience applying statistical analysis, ML, anomaly detection to real-world problems.
• Strong Python skills for data analysis, automation, and production workflows.
• Experience querying and analyzing large datasets with SQL and modern data technologies.
• Ability to communicate results to stakeholders with varying technical levels.

Responsabilidades

• Partner with subject matter experts to define metrics, thresholds, and decision criteria.
• Design, test, and deploy anomaly-detection and pre-emptive-monitoring algorithms.
• Build end-to-end analytical pipelines and dashboards with alerts.
• Create customer-focused visualizations of VIN, software versions, and fleet data.
• Communicate findings clearly to both technical and non-technical audiences.

Conhecimentos

Python

SQL

Statistics

Machine learning

Data visualization

Communication

Formação académica

Bachelor’s degree in Data Science / Statistics / CS / Engineering / Mathematics

Equivalent practical experience

Ferramentas

Azure Data Factory

Databricks

Power BI

Git

Descrição da oferta de emprego

General Motors (GM) in Warren/Austin area seeks a Senior Data Scientist to develop and operationalize data science solutions that identify emerging vehicle, software, and product-quality issues before they become risks.

This role partners with Product Quality, Warranty, Vehicle Engineering, software teams, and others to translate complex questions into trustworthy metrics, detection algorithms, dashboards, and alerts.