Senior Data Scientist

At One Study Team  (a Reify Health company), we specialize in speeding up clinical trials and increasing the chance of new therapies being approved with the ultimate goal of improving patient outcomes. Our cloud-based platform, Study Team, brings research site workflows online and enables sites, sponsors, and other key stakeholders to work together more effectively. Study Team is trusted by the largest global biopharmaceutical companies, used in over 6,000 research sites, and is available in over 100 countries.

Join us in our mission to advance clinical research and improve patient care.

One mission. One team. That’s One Study Team .

As a Senior Data Scientist, you will play a pivotal role in advancing Reify Health’s data-driven solutions for clinical trials. In this position, you will drive the development of statistical models and machine learning algorithms to improve patient enrollment and trial management. You’ll work in a highly regulated healthcare data environment, ensuring compliance with privacy standards while innovating on predictive analytics.

This role involves close collaboration with cross-functional teams (especially ML Engineering) to translate complex data insights into practical, impactful tools for the clinical research community.

• Site Randomization Forecasting:
  Develop/enhance forecasting models for site randomization and enrollment trends, enabling better planning and resource allocation across trial sites.
• Patient Matching/Ranking Algorithms:
  Support projects to build algorithms that intelligently match patients to (or rank patients for) appropriate clinical trials, enhancing recruitment efficiency and patient inclusion.
• Develop Other Advanced Statistical Models:
  Create and refine predictive models (Bayesian inference, regression analysis, time-series forecasting) to address other key clinical trial challenges and improve decision-making.
• AI Monitoring and Bias Detection:
  Implement processes to monitor machine learning models in production, detecting bias or performance drift and ensuring models remain fair, accurate, and compliant.
• Data Pipeline & Tooling Development:
  Build and optimize data pipelines and analytical workflows using tools like AWS Athena, Redshift, Sage Maker, and dbt, enabling scalable model training and deployment.
• Regulatory Compliance in Data Science:
  Ensure all data science practices align with HIPAA, GDPR, and other privacy regulations, integrating compliance considerations into model development and data handling.
• Cross-Functional Collaboration:
  
  Work closely with machine learning engineers, product managers, and other stakeholders to integrate models into products and clearly communicate insights and recommendations.

• Minimum of Master’s or Ph.D. in Statistics, Data Science, Computer Science, or a related quantitative field (or equivalent professional experience).
• Minimum of 5+ years of hands‑on data science or analytics experience, preferably in a healthcare, clinical research, or other highly regulated data environment.
• Statistical & ML Expertise:
  Strong foundation in statistical modeling and machine learning techniques, including experience with Bayesian methods, regression analysis, and time-series forecasting.
• Model Monitoring & Fairness:
  Proficiency in evaluating model performance and bias, with the ability to implement AI monitoring tools and bias mitigation strategies to ensure ethical and reliable outcomes.
• Technical Toolset:
  Advanced programming skills in Python (with libraries such as scikit-learn, PyMC, mlforecast, etc.) and SQL, as well as familiarity with data transformation tools like dbt.
• Cloud & Data Infrastructure:
  Hands‑on experience with cloud-based analytics and ML services, especially AWS tools (Athena for querying, Redshift for data warehousing, Sage Maker for model development/deployment).
• Regulated Data Handling:
  Experience working with sensitive healthcare or clinical trial data under regulations like HIPAA and GDPR, demonstrating a deep commitment to data privacy and security best practices.
• Collaborative Communication:
  Excellent teamwork and meticulous verbal/written…