Senior Clinical Data Scientist

Senior Clinical Data Scientist

Requisition  

Posting Date 19 minutes ago (5/18/2026 5:24 PM)

Job Location(s) West Lafayette IN United States

Position Type Full Time

Company Cook Research Inc.

Category Clinical

We believe in taking care of our people so they can take care of others. As a global, family-owned company that has been improving patients' lives since 1963, we're committed to doing business with integrity and making a positive impact in the communities where we live and work. We're guided by strong ethical standards and core values, and we believe the best ideas come from creating solutions together.

Our company culture values every voice, brings together inclusive teams who collaborate well, and encourages learning and innovation. When you join Cook, you're not just starting a job, you're building a career with purpose, in a company that invests in you.

• Meaningful work & strong values:
  Contribute to improving patient care globally in a company known for high ethical standards and integrity.
• Competitive rewards & security:
  Competitive, performance-related compensation and benefits that support your health and financial wellbeing.
• Flexibility & time off:
  Paid time off, holidays, and hybrid or remote work options for many jobs, where possible.
• Growth & development:
  Learning opportunities, educational assistance, and development programs to help you grow your skills and career.
• Wellbeing & community:
  Health and wellness initiatives, social activities, and community engagement that help you feel connected and supported.

Benefits and programs vary by country and job. Our recruiters can provide more information about the specific benefits and programs available in your location.

The Senior Clinical Data Scientist is an individual contributor responsible for applying advanced analytics, machine learning, AI-driven methodologies, and clinical expertise to generate actionable insights, predictive capabilities, and scalable data solutions.

This Senior Clinical Data Scientist partners with cross-functional stakeholders to translate complex clinical and operational problems into analytical strategies, evaluating data risk and delivering insights that inform decision making related to patient safety, study execution, data integrity, and portfolio-level decisions. The role is expected to demonstrate strong aptitude in applied AI, including identifying, designing, and implementing AI-enabled solutions in a responsible, ethical and governed manner.

• Develop and deploy advanced analytical models, including machine learning, predictive modeling, forecasting, and anomaly detection.
• Apply AI/ML techniques to solve complex business problems and identify patterns, risks and opportunities within large, multi-source datasets.
• Design, build and maintain scalable analytical solutions and reusable data science frameworks.
• Translate analytical findings into clear, accurate and actionable insights tailored for technical and non-technical stakeholders.
• Partner with cross functional teams to ensure insights are actionable and aligned to business priorities.
• Contribute to the development of KPIs, metrics, and performance measurement frameworks in collaboration with cross-functional stakeholders.
• Mentor peers and contribute to building data science and AI/ML capabilities across the organization.
• Apply advanced analytics to patient-level, site-level, and study-level clinical data, processes, and documents to support study design and strategy, execution, oversight, and portfolio insights including potential claims.
• Integrate and analyze data across clinical systems (e.g., EDC, CTMS, eTMF, safety systems, external data sources) to provide a holistic view of site and study performance and data reliability.
• Evaluate data quality, data risk, and data completeness in the context of clinical trial conduct, identifying potential impacts to patient safety and endpoint integrity.
• Ensure analytical approaches align with regulatory authority expectations for electronic records (e.g., data integrity, traceability, reproducibility) and the use of AI in generating outputs.
• Apply knowledge of Good Clinical Data Management Practices (GCDMP), and regulatory authority expectations to ensure data is not only complete, but credible and fit for decision-making.
• Support inspection readiness through well-documented processes and auditable analytical outputs.

• Demonstrated experience applying machine learning and AI techniques in production or near-production environments.
• Experience developing predictive models, classification models, or anomaly detection systems.
• Familiarity with model lifecycle management, including validation, monitoring, and performance evaluation.
• Ability to identify and implement AI-driven automation or decision-support solutions.
• Awareness of ethical, regulatory, and governance considerations in AI/ML approaches, development and deployment within clinical research…