Dexcom Data Scientist Job Openings 2026 – Apply Now!

Qualifications

What makes you successful:

• You have proven experience in a data analyst or data scientist role supporting engineering, R&D, or technical organizations.
• You are proficient in data modeling, querying, and transformation using SQL and NoSQL technologies such as MongoDB – Desired
• You have strong experience developing dashboards and analytics in Power BI and/or Tableau.
• You are comfortable programming for data integration, automation, and analytics workflows.
• You understand engineering data types and workflows across mechanical, electrical, hardware, and firmware development.
• You have experience deploying or supporting AI and machine learning solutions, including integration of third‑party AI tools.
• You are a problem solver who thrives on standardizing processes, improving data integrity, and reducing manual effort.
• You communicate clearly and effectively, collaborating with engineers, data consumers, and leadership.
• You are detail‑oriented, organized, and capable of managing multiple data initiatives in a fast‑paced, regulated environment. You demonstrate an eye for process improvement, with an interest in standardization, efficiency gains, and opportunities for automation within engineering workflows.
• Experience with Onshape is a plus, especially in environments transitioning from traditional CAD tools, along with exposure to CAD data migration or platform adoption efforts.

Where you come in:

• You lead efforts to standardize and automate engineering data pipelines across mechanical, electrical, hardware, and firmware domains.
• You design, model, and integrate structured and unstructured data from multiple engineering and enterprise systems.
• You build and maintain business intelligence dashboards and analytics (e.g., Power BI, Tableau) that translate complex technical data into clear, actionable insights for R&D and leadership through visualizations and executive-level reporting.
• You partner with engineering and IT stakeholders to define data governance, data quality standards, and scalable data management practices.
• You write and maintain queries, transformations, and automations using SQL and related programming languages.
• You support data modeling and storage solutions using platforms such as MongoDB and relational databases.
• You drive the evaluation, pilot, and implementation of AI solutions, including custom models and third‑party platforms, to enhance engineering productivity and insight.
• You analyze and interpret engineering test and validation data using statistical methods to identify trends, variability, and performance drivers across products and systems
• You develop statistical models and summaries to support engineering decision‑making, trade studies, and design verification activities
• You collaborate cross‑functionally to identify opportunities where data analytics and AI can improve engineering processes, quality, and decision‑making.