Software Engineer Intern

Mathematica Inc•Ann Arbor, MI

2d•Hybrid

About The Position

Mathematica applies expertise at the intersection of data, methods, policy, and practice to improve well-being around the world. We collaborate closely with public- and private-sector partners to translate big questions into deep insights that improve programs, refine strategies, and enhance understanding using data science and analytics. Our work yields actionable information to guide decisions in wide-ranging policy areas, from health, education, early childhood, and family support to nutrition, employment, disability, and international development. Mathematica offers our employees competitive salaries and a comprehensive benefits package, as well as the advantages of being 100 percent employee owned. As an employee stock owner, you will experience financial benefits of ESOP holdings that have increased in tandem with the company’s growth and financial strength. You will also be part of an independent, employee-owned firm that is able to define and further our mission, enhance our quality and accountability, and steadily grow our financial strength. Read more about our benefits here: Benefits at a Glance. We’re looking for a curious, technically minded Undergraduate Intern to support platform modernization initiatives. This internship provides hands-on experience as you’ll support the implementation of a cloud-based, database-driven data management and analytics platform. This platform is designed to enhance how data is integrated, transformed, and leveraged for policy decision-making. The Software Engineer Intern will be paired with a mentor during their internship to gain insight into Mathematica’s health policy work and how data supports it. Our 10-week internship starts on June 15 and ends August 21. This position can work remotely or in any of our offices, including Princeton, NJ; Washington, DC; Ann Arbor, MI; Cambridge, MA; Chicago, IL. Mathematica also offers hybrid work options. You’ll directly contribute to production systems, learn modern software engineering and cloud best practices, and better understand how scalable digital infrastructure is designed, built, tested, and deployed. Additionally, interns may be engaged in: Designing, testing, documenting, and maintaining production-level programming that supports data lifecycle management. Developing APIs, backend services, database queries, automation scripts, and internal tools using technologies such as SQL, C#, Python, and related cloud and data platform services. Supporting quality assurance efforts by writing and executing unit, integration, and regression tests; developing testing tools; troubleshooting defects; and participating in code reviews.

Requirements

Currently enrolled in or recently completed an undergraduate program or bootcamp, with an academic record including courses in subjects such as computer science, software engineering, information systems, data engineering, statistics, data science, and/or mathematics. Equivalent years of experience can be substituted.
Demonstrated interest and/or experience building software, tools, platforms, or automated workflows which contribute to projects with a policy/social impact in an academic, extracurricular, or professional setting.
At least two years of experience writing code in one or more programming languages such as Python, C++, C#, Java, JavaScript/TypeScript, Julia, Rust in the academic, extra-curricular, or professional environment.
Experience applying software engineering practices such as version control, code review, debugging, automated testing, documentation, and basic software design principles.
Ability and desire to work independently as part of a geographically dispersed interdisciplinary team. This includes being able to learn from self-guided tutorials, technical documentation, package documentation, and team knowledge-sharing resources, as well as a willingness to continuously learn and contribute to shared engineering practices.
Experience working with databases, SQL, cloud computing environments, APIs, command-line tools, reproducible development workflows, and common software development packages or libraries.

Nice To Haves

Experience with healthcare datasets (for example, Medicare or Medicaid claims and enrollment data).
Data engineering pipelines, DevOps or CI/CD practices, containerization, infrastructure-as-code, product or tool development, production-quality analytics applications, machine learning systems, and responsible technology or algorithmic fairness considerations.

Responsibilities

Support platform modernization initiatives.
Support the implementation of a cloud-based, database-driven data management and analytics platform.
Contribute to production systems.
Learn modern software engineering and cloud best practices.
Understand how scalable digital infrastructure is designed, built, tested, and deployed.
Design, test, document, and maintain production-level programming that supports data lifecycle management.
Develop APIs, backend services, database queries, automation scripts, and internal tools using technologies such as SQL, C#, Python, and related cloud and data platform services.
Support quality assurance efforts by writing and executing unit, integration, and regression tests; developing testing tools; troubleshooting defects; and participating in code reviews.