Data Scientist - Insights and Analytics

Hardware Engineering is seeking a Data Scientist to support the intersection of data engineering and business intelligence - helping build the infrastructure that powers data-driven decisions while delivering analytics and insights that inform strategic direction. The ideal candidate brings a solid foundation in both data pipeline engineering and analytics, with a passion for learning to architect data systems and translating outputs into clear, actionable insights. You'll work closely with senior team members and leadership to support workforce planning and operations analytics, growing your skills across the full data lifecycle while contributing to high-impact projects spanning infrastructure and insight.

Description

You'll work across the data stack - helping build and maintain the infrastructure that enables insight, then using that infrastructure to help answer business questions under the guidance of senior team members. Projects will span pipeline development, data modeling, workforce planning, operational analytics, and strategic initiatives across Hardware Engineering.

This role requires collaboration within a multi-disciplined, geographically distributed data science team, contributing to both the engineering foundation and the analytics layer built upon it, while working with business stakeholders and platform teams to support the end-to-end data lifecycle. You'll participate in business analytics projects through all phases - helping define investigations, exploring data, conducting analysis, and presenting results to business customers.

Responsibilities:

Help design, build, and maintain data pipelines (batch and streaming) and data warehouse models that support the analytical foundation for Hardware Engineering

Contribute to analytical frameworks and dashboards used to evaluate organizational health and support growth planning

Support the data lifecycle - from pipeline development and data modeling through to insight delivery - helping ensure data quality, reliability, and accessibility

Help inform decisions across the HWE organization, from workforce planning to operational efficiency, through presentations, visual dashboards, and reports

Assist in building forecasting models for engineering resource needs, helping translate technical findings into recommendations for stakeholders

Help implement data models, schemas, and transformation logic that bridge infrastructure capabilities with business needs, under guidance from senior team members