Senior Data Scientist

Overview

Senior Data Scientist to drive the development of statistical models and machine learning algorithms that improve patient enrollment and trial management for clinical trials, working in a highly regulated healthcare data environment.

What you'll do

• Develop and enhance forecasting models for site randomization and enrollment trends, enabling better planning and resource allocation across trial sites.
• Support projects to build algorithms that intelligently match patients to, or rank patients for, appropriate clinical trials.
• Create and refine predictive models (Bayesian inference, regression analysis, time-series forecasting) to address key clinical trial challenges and improve decision-making.
• Implement processes to monitor machine learning models in production, detecting bias or performance drift and ensuring models remain fair, accurate, and compliant.
• Build and optimize data pipelines and analytical workflows using tools like AWS Athena, Redshift, SageMaker, and dbt, enabling scalable model training and deployment.
• Ensure all data science practices align with HIPAA, GDPR, and other privacy regulations, integrating compliance considerations into model development and data handling.
• Work closely with machine learning engineers, product managers, and other stakeholders to integrate models into products and clearly communicate insights and recommendations.

What you'll need

• Minimum of a 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.
• Strong foundation in statistical modeling and machine learning techniques, including experience with Bayesian methods, regression analysis, and time-series forecasting.
• Proficiency in evaluating model performance and bias, with the ability to implement AI monitoring tools and bias mitigation strategies.
• 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.
• Hands-on experience with cloud-based analytics and ML services, especially AWS tools (Athena, Redshift, SageMaker).
• 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.
• Excellent teamwork and meticulous verbal/written communication abilities, with a track record of partnering with engineering and product teams to translate data science work into actionable business solutions.

Nice to have

• Experience in a healthcare, clinical research, or other highly regulated data environment.
• Understanding of clinical research or health-tech environments, including insight into clinical trial operations and a passion for improving patient outcomes through data.

Details

• Location: Remote within the United States; 100% of work performed in a remote office environment.
• Travel: Less than 10% travel requirement; occasional planned travel may be required.
• Physical demands: ability to use keyboards and other computer equipment.
• Employment type: full-time team members.
• Care Access is unable to sponsor work visas at this time.