Note: The job is a remote job and is open to candidates in USA. Care Access works to make health and medical research more accessible through research locations, mobile clinics, clinicians, partnerships, and technology. The Senior Data Scientist will develop statistical models and machine learning algorithms for clinical trials, improve patient enrollment and trial management, monitor model fairness and performance, and collaborate with engineering and product teams in a regulated healthcare data environment.
Responsibilities
- 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, SageMaker, 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
Skills
- 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 to ensure ethical and reliable outcomes
- 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 for querying, Redshift for data warehousing, SageMaker for model development/deployment)
- 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
- Understanding of clinical research or health-tech environments
- 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
- Including insight into clinical trial operations and a passion for improving patient outcomes through data
- Preferably in a healthcare, clinical research, or other highly regulated data environment
Benefits
- Paid Time Off (PTO) and Company Paid Holidays
- 100% Employer paid medical, dental, and vision insurance plan options
- Health Savings Account and Flexible Spending Accounts
- Bi-weekly HSA employer contribution
- Company paid Short-Term Disability and Long-Term Disability
- 401(k) Retirement Plan, with Company Match
- Remote within the United States; 100% of work performed in a remote office environment
Company Overview