Global Data Science & ML Lead (Remote)

Dexcom Inc.; San Diego (CA); On-site; USD 142,000 - 236,000; Full time

Benefits offered by this job

Full benefits program

Global growth opportunities

Career development programs

Competitive compensation

Job summary

Dexcom Inc. seeks a senior leader to guide a global team of data scientists and engineers in developing, validating, and deploying machine learning models that support post-market surveillance.

You will drive experimentation, analytics, and data product delivery across the enterprise, ensuring high data integrity and scalable solutions. The role emphasizes collaboration with cross-functional stakeholders, adoption of best practices, and clear reporting to senior leadership on product metrics and

Qualifications

• Typically requires a Bachelor’s degree with 8-12 years of industry experience.
• Requires a degree in a technical discipline.
• 2-5 years of previous management or lead experience.

Responsibilities

• Lead and manage global data scientists and engineers.
• Oversee the design, development, validation, and deployment of machine learning models.
• Guide experimentation, hypothesis testing, and statistical analysis initiatives.
• Promote data governance, reporting standards, and documentation.
• Define and execute the data science and engineering roadmap with regulatory compliance.

Skills

Leadership

Cross-functional collaboration

Communication with leadership

Data-driven decision making

End-user mindset

Education

Bachelor’s degree in a technical discipline

Tools

GCP functions

BigQuery

DBT

SQL

Python

GitHub / version control

Job description

Dexcom Inc. seeks a senior leader to guide a global team of data scientists and engineers in developing, validating, and deploying machine learning models that support post-market surveillance.

You will drive experimentation, analytics, and data product delivery across the enterprise, ensuring high data integrity and scalable solutions. The role emphasizes collaboration with cross-functional stakeholders, adoption of best practices, and clear reporting to senior leadership on product metrics and