Intern, Advanced Analytics, Data Science & AI

Biogen•Cambridge, MA

10h•$33 - $33

About The Position

About the Role: This application is for a 12-week internship role from June - August 2026. Resume review begins in February 2026. As an intern, you will work at the intersection of research, analytics, and strategy, partnering closely with experienced data scientists, analytics leaders, and business stakeholders. You will help frame complex questions, design and test advanced models, and translate results into clear, actionable insights. This role offers a highly collaborative environment and exposure to high‑impact problems while allowing room for academic rigor, experimentation, and learning.

Requirements

Legal authorization to work in the U.S.
At least 18 years of age prior to the scheduled start date.
Currently enrolled in an accredited community college, college, university or skills program/apprenticeship.
Experience with machine learning technology, such as big data stack, Python, R, and visualization techniques.
Strong written and verbal communication skills.
PhD candidate focusing in one of the following: engineering, economics, statistics, computer science, or a related quantitative field.

Nice To Haves

Experience with both traditional SQL and modern NoSQL data stores, including SQL, and large-scale distributed systems such as Hadoop or working in Snowflake/Databricks.

Responsibilities

Assist in end-to-end delivery of data science insights, from framing the business question, designing the solution, and delivering recommendations.
Collaborate within the insights & analytics team, coordinating efforts with counterparts to develop and execute a comprehensive brand analytics plan.
Deliver consolidated insights and actionable recommendations to US Commercial teams, ensuring alignment with strategic objectives.
Work closely with cross-functional teams to ensure seamless integration of brand analytics insights into decision-making processes and strategic initiatives.
Continuously evaluate and enhance existing brand/TA data science capabilities, identifying opportunities for optimization and innovation to drive greater business impact and ROI.
Stay up to date with the latest advancements in data science and AI, applying them to improve processes and outcomes.
Assist in building university partnerships for driving innovation and leading-edge research techniques.
Build strong relationships with key stakeholders across the enterprise, effectively communicating the value proposition of data science and fostering a culture of data-driven decision-making.
Ensure compliance with data privacy and security regulations and maintain a high level of data integrity.