Co-op, Data Science & AI Innovation

Summary

Biogen is a biotechnology company focused on delivering life-changing medicines through innovation and collaboration. The Co-op will develop AI-powered data science solutions for pharmaceutical R&D, including machine learning models, data pipelines, dashboards, and decision-support tools across the solution lifecycle.

Responsibilities

• 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
• 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

Skills

• 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
• 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
• Currently pursuing a Master's degree in Data Science, Statistics, Bioinformatics, Computer Science, Computational Biology, or related field
• Experience developing AI-powered applications, decision-support systems, or data products
• Experience with Monte Carlo simulation, optimization, forecasting, or decision science methodologies
• Familiarity with cloud platforms, GitHub, CI/CD pipelines, k8s, containerization, or Linux environments
• Experience with data visualization and product development frameworks such as Streamlit, Power BI, or similar technologies
• Experience in pharmaceutical, biotechnology, healthcare, quality, compliance, or R&D portfolio analytics
• Demonstrated interest in reproducing and implementing state-of-the-art AI and machine learning research

Qualifications

Must Haves

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

Nice to Haves

• Experience developing AI-powered applications, decision-support systems, or data products
• Experience with Monte Carlo simulation, optimization, forecasting, or decision science methodologies
• Familiarity with cloud platforms, GitHub, CI/CD pipelines, k8s, containerization, or Linux environments
• Experience with data visualization and product development frameworks such as Streamlit, Power BI, or similar technologies
• Experience in pharmaceutical, biotechnology, healthcare, quality, compliance, or R&D portfolio analytics
• Demonstrated interest in reproducing and implementing state-of-the-art AI and machine learning research

Benefits

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