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About Dexcom

Founded in 1999, Dexcom, Inc. (NASDAQ: DXCM), develops and markets Continuous Glucose Monitoring (CGM) systems for ambulatory use by people with diabetes and by healthcare providers for the treatment of people with diabetes. The company is the leader in transforming diabetes care and management by providing CGM technology to help patients and healthcare professionals better manage diabetes. Since the company’s inception, Dexcom has focused on better outcomes for patients, caregivers, and clinicians by delivering solutions that are best in class—while empowering the community to take control of diabetes. Dexcom reported full-year 2020 revenue of $1.9B, a growth of 30% versus 2019. Headquartered in San Diego, California, with additional offices in the U.S., Europe, and Asia Pacific, the company employs over 6,000 people worldwide.



As a data science intern, you will be a key contributor to Dexcom’s core Data Science Team, collaborating to serve as the center of a best-in-class data science capability that augments and applies the whole of Dexcom’s data assets to drive value creation across the business, develop innovative data products, and enable a tailored Dexcom experience for all of our customers. You will be working with the latest big data technologies and cloud computing platforms to query real-world data for commercial and clinical insights, support ad hoc data requests, develop ingestion pipelines for data modeling, and operationalize predictive model pipelines in a collaborative environment.

Essential Duties and Responsibilities:

  • Work under the guidance of Data Science mentor to write data ingestion pipelines, perform ad hoc analytics, operationalize model pipelines, and communicate results to data science team.
  • Use techniques from statistical analysis and predictive modeling to build knowledge of Dexcom products, processes, and customers.
  • Query and analyze data in support of existing apps and other products in commercial use.
  • Support stakeholders across the business by executing advanced forms of analytics on diabetes-centric and other Dexcom data.
  • Work with team under agile development methods.
  • Munge, clean and interpret raw data into analysis-ready data sets.
  • Assist in requirements definition, project scoping, timeline management, and results documentation to ensure professional relationship management.
  • Perform high quality research in collaboration with other functional teams at Dexcom into the patterns and properties of diabetes centric data from the individual to population scale to inform product, digital services and business development.
  • Document code in shared repositories and communicates project results to department on completion of program.
  • Assist in executing projects that further the improvement and efficiency of the department.

Required Qualifications

  • Familiarity working with databases and distributed computing platforms and their query interfaces.
  • Familiarity working with high level programming languages.
  • Knowledge of statistical methods.
  • Familiarity with algorithms and the mathematical methods used to extract information from data.
  • Familiarity provisioning compute resources with tools and software for exploratory data science discovery work.
  • Good understanding of database systems
  • Familiarity with visualization software and techniques.
  • A team player with demonstrated track record of collaboration.
  • Capable of conducting independent research, motivated by hard technical challenges.
  • Results-driven, self-motivated, self-starter.
  • Excellent written and verbal communications skills, with a proven ability to translate complex methodologies and analytical results to business insights.

Preferred Qualifications

  • Experience working with Python.
  • Experience working with GCP BigQuery or SQL.
  • Familiarity with Python libraries for math and statistics.
  • Working knowledge of enterprise cloud tools for big data analysis such as Google Cloud, AWS, and Azure
  • Familiarity with Jupyter Notebook, or Jupyter Lab
  • Familiarity with statistical inference, data mining, pattern recognition or machine learning.
  • Familiarity working with column store and NoSQL databases.
  • Familiarity with tools in the Hadoop eco system like HDFS, Hive, MapReduce.
  • Familiarity with queuing systems and ability to work efficiently in a shared compute environment.
  • Ability to prepare high quality technical figures for publication in industry and scientific journals.
  • Familiarity working cross functionally with teams deployed across the US and internationally.
  • Entrepreneurial experience at start-ups and academic labs.
  • Experience in continuous glucose monitoring and related data.

Experience and Education

  • Typically requires 0-2 years of related experience and a High school diploma/certificate or equivalent.
  • Currently pursuing a bachelor’s degree (BS) or higher in a technical field such as data science, computer science, computer programming, information technology, or similar.