Co-Op, Biometrics

Moderna; Cambridge (MA); On-site; USD 28,000 - 83,000; Part time

Benefits offered by this job

Premium mindfulness

Commuter benefits

Paid time off

Job summary

Moderna offers a co-op opportunity in Cambridge, MA, focusing on AI-enabled statistics, clinical data science, and technology development within the SiDA team. The role emphasizes hands-on AI engineering, data analytics, and scalable pipelines to support statisticians and clinical teams.

You'll explore LLMs, agentic workflows, model post-training, and visualization tools, aiming to reduce repetitive work and accelerate insights within regulated clinical research workflows.

Qualifications

• Strong background in statistics and data analysis for clinical data.
• Proficient in Python; experience with R is a plus.
• Familiarity with cloud platforms, containers, and SQL.
• Interest in GenAI/LLMs and AI-based workflows.
• Ability to translate AI outputs into practical models.

Responsibilities

• Develop and evaluate AI/ML and agentic solutions for clinical data analysis, statistical programming, and workflow automation.
• Explore LLM post-training, adaptation, and evaluation approaches to improve model performance.
• Design agentic workflows with human oversight, traceability, and reproducibility for regulated environments.
• Build scalable AI pipelines integrating clinical, statistical, and translational datasets.
• Create interactive data visualizations, dashboards, and analytics to accelerate insights.
• Collaborate with statisticians, data scientists, and engineers to translate needs into solutions.
• Explore opportunities to automate data lifecycle tasks including processing, QC, and reporting.
• Contribute to documentation, evaluation considerations, and reusable AI capabilities.

Skills

Python

R language

Cloud platforms

Containerization

SQL

Statistical modeling

Communication

Teamwork

AI/ML knowledge

Education

Master's in stats

Tools

Docker

Jupyter

SQL tooling

Job description

The Role

This is a co-op opportunity based in Cambridge, MA from January 18, 2027 – June 25, 2027. Applicants must be available for the full duration of the co-op term.

The Statistical Innovation & Data Analytics (SiDA) team is advancing AI-enabled statistical and clinical data solutions to accelerate data-driven decision-making, improve operational efficiency, and strengthen regulatory readiness across clinical development programs.

Role

This role provides hands-on experience at the intersection of statistics, clinical data science, and AI engineering, with opportunities to work on:

• Clinical and statistical data analytics, including EDC, SDTM, ADaM, and translational data
• AI/ML research and applied statistical modeling for clinical development use cases
• LLM and agentic AI development, including domain-specific agents, tool integration, retrieval, and workflow orchestration
• Local and domain-specific model post-training, evaluation, and optimization for statistical and clinical applications
• AI-assisted statistical programming and analytics, exploring opportunities to automate and augment existing biometrics workflows
• Scalable and governed AI solutions, transitioning promising prototypes toward production-oriented applications that meet clinical data, security, quality, and compliance requirements

The student will contribute to the design, development, evaluation, and implementation of AI-enabled capabilities that support statisticians, statistical programmers, data scientists, and clinical development teams.

The role is particularly suited for students interested in going beyond general-purpose AI experimentation to understand how AI can be tailored, evaluated, and operationalized for statistical and clinical research workflows, with the goal of reducing repetitive work, accelerating time to insight, and enabling more agile use of clinical data.

Here’s What You’ll Do

• Develop and evaluate AI/ML and agentic solutions for clinical data analysis, statistical programming, and workflow automation, including tool-calling, RAG, and skill-based agent architectures.
• Explore LLM post-training, adaptation, and evaluation approaches to improve model performance for statistical and clinical research use cases.
• Design agentic workflows with appropriate human oversight, traceability, and reproducibility for use in regulated clinical development environments.
• Build scalable and modular AI pipelines that integrate clinical, statistical, and translational datasets.
• Develop interactive data visualizations, dashboards, and analytical applications to accelerate clinical insights and decision-making.
• Collaborate with statisticians, statistical programmers, data scientists, and scientists to translate clinical and business needs into practical technical solutions.
• Explore opportunities to automate and augment the clinical data lifecycle, including data processing, analysis, QC, interpretation, and reporting.
• Contribute to documentation, evaluation, validation considerations, and reusable AI capabilities that can scale across studies and programs.

Here’s What You’ll Bring to the Table (Preferred Qualifications)

• Master, doctoral or advanced undergraduate Student in statistics, biostatistics, computational biology, health informatics, data science or computer science related quantitative disciplines.
• Excellent statistical knowledge and quantitative skills with the ability to apply the knowledge to solve scientific and clinical problems.
• Experience in coding in Python (required) and R (preferred); demonstrated ability in cloud computing platforms, containerization, backend development, and SQL.
• Experience or demonstrated interest in GenAI/LLMs, machine learning, agentic systems, model post-training, or AI application development.
• Familiarity with one or more of the following is a plus: cloud computing, containerization, APIs/backend development, RAG, model evaluation, or AI deployment.
• Experience developing data visualizations, analytical applications, dashboards, or reusable computational tools is preferred.
• Interest in building practical, reliable, and scalable AI solutions for clinical or biomedical research.
• Strong analytical thinking, engineering mindset, curiosity, and written and verbal communication skills.
• Ability to learn quickly, work across disciplines, and translate emerging AI technologies into practical solutions.

Our Working Model

As we build our company, we have always believed an in-person culture is critical to our success. Moderna champions the significant benefits of in-office collaboration by embracing a 70/30 work model. This 70% in-office structure helps to foster a culture rich in innovation, teamwork, and direct mentorship. Join us in shaping a world where every interaction is an opportunity to learn, contribute, and make a meaningful impact.

Moderna is a smoke-free, alcohol-free, and drug-free work environment.

Pay & Benefits

• Free premium access to meditation and mindfulness classes
• Subsidized commuter benefits
• Generous paid time off, including vacation, sick time, holidays, volunteer days, and a discretionary year-end shutdown
• Location-specific perks and extras

The salary range for this role is $20.00 - $60.00. This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An individual’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, performance, and business or organizational needs.

The successful candidate may be eligible for an annual discretionary bonus, other incentive compensation, or equity award, subject to company plan eligibility criteria and individual performance.

The successful candidate may be eligible for an annual discretionary bonus, other incentive compensation, or equity award, subject to company plan eligibility criteria and individual performance.

About Moderna

Since our founding in 2010, we have aspired to build the leading mRNA technology platform, the infrastructure to reimagine how medicines are created and delivered, and a world-class team. We believe in giving our people a platform to change medicine and an opportunity to change the world.

By living our mission, values, and mindsets every day, our people are the driving force behind our scientific progress and our culture. Together, we are creating a culture of belonging and building an organization that cares deeply for our patients, our employees, the environment, and our communities.

Equal Opportunities

Moderna is committed to equal employment opportunity and non-discrimination for all employees and qualified applicants without regard to a person’s race, color, sex, gender identity or expression, age, religion, national origin, ancestry or citizenship, ethnicity, disability, military or protected veteran status, genetic information, sexual orientation, marital or familial status, or any other personal characteristic protected under applicable law. Moderna is a place where everyone can grow. If you meet the Basic Qualifications for the role and you would be excited to contribute to our mission every day.

Moderna is an E-Verify Employer in the United States. We consider qualified applicants regardless of criminal histories, consistent with legal requirements.

Accommodations

We’re focused on attracting, retaining, developing, and advancing our employees. By cultivating a workplace that values diverse experiences, backgrounds, and ideas, we create an environment where every employee can contribute their best.

Moderna is committed to offering reasonable accommodations to qualified job applicants with disabilities. Any applicant requiring an accommodation in connection with the hiring process and/or to perform the essential functions of the position for which the applicant has applied should contact the Accommodations team at [e-mail].

Export Control Notice

Export Control Notice This position may involve access to technology or data that is subject to U.S. export control laws, including the Export Administration Regulations (EAR). As such, employment is contingent upon the applicant’s ability to access export-controlled information in accordance with U.S. law. Only U.S. persons (U.S. citizens, U.S. lawful permanent residents, asylees, or refugees) are currently eligible to access such information without an export license. Candidates who do not meet these criteria may still be considered, contingent on the company’s ability to obtain any required export control license.