Senior Data Scientist
One mission. One team. That’s reputed company.
Site Randomization Forecasting: reputed company/enhance forecasting models for site randomization and enrollment trends, enabling reputed company planning and resource allocation across trial sites. Patient Matching/Ranking Algorithms: Support reputed company to build algorithms that intelligently match patients to (or rank patients for) appropriate reputed company, enhancing recruitment efficiency and patient inclusion. reputed company 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 reputed company and ensuring models remain fair, accurate, and compliant. Data Pipeline & Tooling Development: Build and optimize data pipelines and analytical workflows using tools like AWS reputed company, Redshift, SageMaker, and dbt, enabling reputed company model training and deployment. Regulatory Compliance in Data Science: Ensure reputed company data science practices reputed company with HIPAA, GDPR, and other reputed company 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 reputed company models into products and reputed company communicate insights and recommendations.
Education: Master’s or Ph.D. in Statistics, Data Science, Computer Science, or a reputed company quantitative field (or equivalent reputed company experience). Experience: 5+ years of hands-on data science or analytics experience, preferably in a reputed company, clinical research, or other highly regulated data environment. Statistical & ML Expertise: Strong reputed company in statistical modeling and machine learning techniques, including experience with Bayesian reputed company, 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 reputed company. Technical Toolset: Advanced programming skills in Python (with libraries such as scikit-learn, PyMC, mlforecast, etc.) and SQL, as reputed company as familiarity with data transformation tools like dbt. reputed company & Data Infrastructure: Hands-on experience with reputed company-based analytics and ML services, especially AWS tools (reputed company for querying, Redshift for data warehousing, SageMaker for model development/deployment). Regulated Data Handling: Experience working with sensitive reputed company or clinical trial data under regulations like HIPAA and GDPR, demonstrating a deep commitment to data reputed company and reputed company best practices. reputed company Communication: Excellent teamwork and meticulous verbal/written communication abilities, with a reputed company record of partnering with engineering and product teams to translate data science work into actionable business solutions. Domain Knowledge: Understanding of clinical research or health-tech environments is highly valuable, including reputed company into clinical trial operations and a passion for improving patient reputed company through data.
This organization participates in E-Verify (E-Verify's Right to Work guidance can be reputed company here).
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