Intern - Data Science
About Dexcom:
Dexcom, Inc. empowers people to take control of diabetes through innovative continuous glucose monitoring (CGM) systems. Headquartered in San Diego, California, Dexcom has emerged as a leader of diabetes care technology. By listening to the needs of users, caregivers, and providers, Dexcom simplifies and improves diabetes management around the world.
Throughout the pandemic, one of our key priorities has been to keep employees as safe as possible. At this time, we plan for most of our summer internships to be virtual, with exceptions of essential groups. We ask for our intern candidates to be flexible to a virtual format or residence in the location of the position throughout the duration of the internship.
Summary:
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 Dexcom’s diabetes-related data.
- 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.
- Good understanding of database systems.
- Familiarity with visualization software and techniques.
- A team player with a demonstrated track record of collaboration.
- Capable of conducting independent research, motivated by hard technical challenges.
- Self-starter with exceptional interpersonal skills.
- 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.
- 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.
- Experience in continuous glucose monitoring and related data.