[Hiring] Co-op, Data Science & AI Innovation @Biogen

Role Description

This application is for a 6-month student role from January - June 2027. Resume review begins in October 2026.

Portfolio Data & Digital Innovation (PDDI) is a multidisciplinary team dedicated to transforming how Development leverages data, technology, and artificial intelligence to make faster, better-informed decisions. We bring together expertise in portfolio analytics, data management, AI/ML innovation, Planisware technology, and digital product delivery to create scalable solutions that improve portfolio visibility, streamline operations, and accelerate decision-making.

As a member of the Portfolio Data & Digital Innovation (PDDI) team, you will help shape the future of data-driven decision making across Biogen's R&D portfolio. Working alongside data scientists, portfolio strategists, data engineers, and business leaders, you will develop AI-powered solutions that improve portfolio visibility, accelerate decision-making, enhance data quality, and streamline operational workflows. You will contribute across the full solution lifecycle, from data acquisition and engineering to model development, deployment, monitoring, and continuous improvement.

• Collaborate with data scientists, portfolio analysts, and subject matter experts to develop and deploy innovative AI and analytics solutions.
• Design and implement machine learning, predictive analytics, and decision-support models that address real-world portfolio and operational challenges.
• Develop interactive dashboards, reporting tools, and data products that translate complex data into actionable insights.
• Research and evaluate emerging AI, machine learning, and agentic AI technologies and identify opportunities to apply them within pharmaceutical R&D.
• Partner with stakeholders across Development, Portfolio Management, and Operations to understand business needs and deliver scalable, high-impact solutions.
• Contribute to the design and maintenance of data pipelines, AI platforms, and software products that support enterprise decision-making.
• Promote responsible AI practices, model transparency, and continuous learning through experimentation and innovation.

Example projects may include:

• Building AI agents that automate portfolio reporting, risk identification, and data reconciliation workflows.
• Developing predictive and prescriptive analytics to support portfolio prioritization and strategic planning.
• Developing scalable data pipelines and ETL processes that integrate data from Planisware, quality systems, financial systems, and other enterprise platforms.
• Supporting the design, optimization, and governance of Biogen's Snowflake-based data ecosystem, enabling trusted, AI-ready data products and analytics.
• Creating machine learning models and decision-support tools for resource forecasting, quality analytics, and operational intelligence.
• Developing Project FORWARD capabilities that connect data, AI, and workflow automation to enable a more proactive and intelligent portfolio management ecosystem.

Qualifications

• Proficiency in Python, R, or another programming language commonly used for data science and analytics.
• Strong foundation in machine learning, statistics, and data analysis.
• Familiarity with NLP, LLMs, generative AI, and their underlying methodologies.
• Experience with modern machine learning and deep learning frameworks such as PyTorch, TensorFlow, Hugging Face, or similar platforms.
• Experience building and maintaining data pipelines, ETL workflows, and data integration processes.
• Proficiency in SQL and experience working with enterprise-scale relational and cloud-based data platforms.
• Familiarity with Snowflake, Databricks, or other modern cloud data warehousing technologies.
• Understanding of data modeling concepts, including dimensional modeling, star schemas, and data architecture best practices.
• Ability to communicate technical concepts and analytical findings to both technical and non-technical audiences.
• Strong problem-solving skills and a desire to work collaboratively in a multidisciplinary environment.
• Passion for learning, experimenting with emerging AI technologies, and applying them to business challenges.

Requirements

• Legal authorization to work in the U.S.
• At least 18 years of age prior to the scheduled start date.
• Be currently enrolled in an accredited community college, college, university or skills program/apprenticeship.

Education Requirements

• Currently pursuing a Master’s degree in Data Science, Statistics, Bioinformatics, Computer Science, Computational Biology, or related field.

Benefits

• Company paid holidays
• Commuter benefits
• Employee Resource Groups participation
• 80 hours of sick time per calendar year