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.

Minimum Qualifications

BS/BA in Computer Science, Software Engineering, Data Science, or equivalent degree 1-3 years of experience in business analytics, including surfacing insights, exploring data trends, and communicating findings to stakeholders 1-3 years of experience with data pipelines, data modeling, or data warehousing concepts, ideally in cloud-based platforms like AWS or Snowflake Working proficiency in Python for data analysis and pipeline tasks, including familiarity with pandas, NumPy, and data visualization libraries Eager problem-solver comfortable working through ambiguity, managing tasks, and collaborating with senior team members to deliver projects Exposure to cloud data platforms (AWS, Snowflake) and/or pipeline orchestration tools (e.g., Airflow, dbt) is a plus

Preferred Qualifications

Coursework or project experience with scikit-learn or basic forecasting/statistical modeling Familiarity with dbt, Apache Spark, or similar data transformation frameworks Experience collaborating on team projects involving data quality or monitoring Interest in prompt engineering or using LLMs for data analysis and automation workflows Familiarity with JavaScript for data visualization (e.g., D3.js, Observable) is a plus