Co-op, Data Science

Biogen

2d•$23 - $29

About The Position

This application is for a 6-month student role from January - June 2027. Resume review begins in October 2026. SPARQ TADI are seeking a motivated, intellectually curious Data Scientist Co-op to support data science, analytics, and artificial intelligence initiatives across drug development. This role is designed for a college degree–seeking student who wants hands-on experience applying statistical, machine learning, and data engineering methods to real-world challenges in biopharmaceutical research and development. The co-op will work alongside data scientists and subject matter experts to transform complex regulatory, R&D quality/compliance, drug safety and/or non-clinical safety data into actionable insights that help improve drug development decision-making, efficiency, quality, and patient impact.

Requirements

Demonstrated proficiency in at least one programming language commonly used for data science, such as Python, R, or SQL.
Foundational understanding of statistics, machine learning, data visualization, and data preparation techniques.
Interest in drug development, biotechnology, pharmaceutical research, clinical development, regulatory science, or healthcare analytics.
Strong analytical thinking, problem-solving skills, attention to detail, and willingness to learn complex scientific and operational domains.
Ability to communicate technical concepts clearly and collaborate effectively with cross-functional partners.
Comfort working independently on assigned deliverables while actively seeking feedback and guidance from mentors and project teams.
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.
Currently pursuing a bachelor’s or master’s degree in data science, statistics, biostatistics, computer science, bioinformatics, computational biology, engineering, mathematics, public health, life sciences, or a related quantitative field.

Nice To Haves

Building LLM Chatbots to search in unstructured data repositories to find answers to regulatory authority queries.
Human in the loop content and document generation
Build agents to can interrogate processes like an auditor or inspector
Develop SOP/Guidance to ensure quality and oversight of AI with team

Responsibilities

Collaborate with data scientists and stakeholders to define analytical questions and translate business or scientific needs into data-driven solutions.
Prepare, clean, integrate, and analyze structured and unstructured data from regulatory, R&D quality/compliance, drug safety and/or non-clinical safety sources.
Create dashboards, visualizations, user interfaces, and/or reports that enable data driven decision making to technical and non-technical audiences.
Research emerging applications of artificial intelligence, machine learning, natural language processing, and advanced analytics in pharmaceutical research and development.
Contribute to reusable data pipelines, code libraries, model documentation, and analytical workflows that promote quality, transparency, scalability, and reproducibility.
Present findings, recommendations, and technical approaches to project teams and stakeholders in a clear, concise, and professional manner.