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.

What You’ll Be Working On

• 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. 

What You Bring to OneStudyTeam

• Education: Master’s or Ph.D. in Statistics, Data Science, Computer Science, or a related quantitative field (or equivalent professional experience). 
• Experience: 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, SageMaker 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 communication abilities, with a track 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 insight into clinical trial operations and a passion for improving patient outcomes through data.

The expected salary range for this role is $140,000 - $190,000 USD per year for full time team members.

#LI-Remote

By joining our team as a Senior Machine Learning Engineer, you will play a pivotal role in building cutting-edge AI products that directly impact how new therapies reach patients. We’re looking for an experienced ML engineer who is passionate about turning advanced AI research into scalable, real-world solutions. You thrive on solving complex problems, pay close attention to detail, and consistently seek to automate and improve processes. You shine as a collaborator and excel as an individual contributor, with the courage to tackle challenging problems and the humility to learn and adapt. Your initiative and discipline allow you to thrive while working remotely, and your high degree of empathy and communication skills makes you the kind of colleague everyone wants on their team. As an integral member of our fast-growing organization, you will leverage AI to transform clinical research and improve patient care.

What You’ll Be Working On:

• Build and deploy AI-driven products that accelerate clinical trials and improve patient outcomes. Your work will deliver scalable machine learning solutions to complex, real-world problems in clinical research.
• Develop advanced ML models and LLM-powered agents for critical use cases like patient recruitment, enrollment forecasting, and study feasibility. You’ll also help expand our AI knowledge base architecture to support these innovative solutions.
• Leverage modern cloud tools and MLOps best practices to build robust data pipelines and deploy models at scale. You’ll use technologies like Python (and Clojure), AWS services (Athena, Bedrock, SageMaker, etc.), dbt, Prefect, and CI/CD automation with monitoring to ensure models are reliable and up-to-date.
• Collaborate across teams of data scientists, product managers, designers, engineers, and domain experts to integrate AI capabilities into our platform (including Care Access products). Ensure these AI solutions seamlessly support and enhance clinical research workflows for end-users.
• Continuously learn and innovate. Stay up-to-date with the latest developments in ML/AI (LLMs, NLP, probabilistic modeling, etc.) and proactively bring new ideas to the team. You’ll have the freedom to experiment with cutting-edge techniques and turn promising prototypes into production features that drive our mission forward.

What You’ll Bring to OneStudyTeam:

• Extensive ML engineering experience: 5+ years of hands-on experience building and deploying machine learning solutions in production at scale. Proven ability to implement end-to-end ML pipelines from data ingestion to model serving for real-world applications used by real people.
• Strong programming and data skills: Proficiency in Python and its ML ecosystem (pandas, scikit-learn, TensorFlow/PyTorch), with clean and efficient coding practices. Comfortable working with large datasets, writing complex SQL queries, and leveraging modern data processing frameworks. Experience with functional programming (e.g. Clojure) is a plus but not required.
• Cloud and MLOps expertise: Experience with modern cloud infrastructure (AWS or similar) and containerization tools like Docker. Familiarity with MLOps best practices such as CI/CD pipelines, automated testing, and monitoring model performance/data drift to ensure reliable, scalable deployments.
• Deep ML/AI knowledge: Strong understanding of machine learning fundamentals (model selection, training, evaluation, feature engineering) and statistical modeling. Familiarity with NLP and large language models is important.
• Analytical problem-solving: Ability to break down complex problems and devise effective, efficient ML solutions. You balance pragmatic engineering with scientific rigor, ensuring models are not only accurate but also performant and maintainable in production.
• Mission-driven and business-focused mindset: A passion for our mission to speed up clinical trials and improve patient outcomes. Empathy for patients, clinicians, and researchers drives you to build unbiased AI solutions.

The expected salary range for this role is $140,000 - $190,000 USD per year for full time team members.