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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Manager Data Science - **Company:** Dexcom, Inc. - **Location:** San Diego, CA, United States (Remote available) - **Experience:** Experienced - **Salary:** $141,800.0 - $236,400.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, BigQuery, Data Architecture, Data Governance, Data Integrity, Data Systems, Github, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, SQL Databases, Data Management, Software Version Control - **Published:** August 11, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=1f1e31e971908c9f ## About the Role * You embrace innovation, with experience or interest in automation, AI, and modern data science practices. * You demonstrate strong analytical and data-driven decision-making skills, leveraging metrics and dashboards to improve outcomes. * You have current expertise in GCP functions and Big Query. * You are also an expert in DBT, SQL and python . * You have experience with GitHub or similar version control software. * You excel in leading global, cross-functional teams and driving collaboration across multiple stakeholders and time zones. * You are an effective communicator who can engage both technical teams and executive leadership with clarity and confidence. * You have a strong end-user-first mindset, with a passion for improving end-user experience and service quality., * 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 Remote Workplace : Your location will be a home office; y ou are not required to live within commuting distance of your assigned Dexcom site (typically 75 miles/120km). If you reside within commuting distance of a Dexcom site (typically 75 miles/120km) a hybrid working environment may be available. Ask about our Flex workplace option . ## Description The Dexcom Post Market Surveillance Data team is a multidisciplinary team responsible for developing, deploying, and scaling advanced analytics, machine learning models, and data products that drive the delivery of actionable post market product performance data across the enterprise. We operate in a fast-paced, mission-critical environment where reliability, efficiency, and timely escalations are paramount . As part of the Data Science and Engineering team, t his role combines strategic leadership, technical expertise , and people management to deliver innovative data solutions while ensuring robust, scalable, and reliable data platforms. Where you come in : * You will lead and manage global, data scientists and engineers , ensuring high-quality, reliable access to data. * You will o versee the design, development, validation, and deployment of machine learning models . * You will guide experimentation, hypothesis testing, and statistical analysis initiatives. * You will recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation . * You will drive adoption of data architecture standards and engineering best practices. * You will define and execute the data science and engineering roadmap while adhering to data governance and regulatory compliance policies. * You will report out to senior leadership product metrics and patient risk data helping to identify areas of improvement. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Making Data Warehouses fast. 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