• Analyse marketplace behaviour to uncover insights that improve supplier and buyer conversion • Interpret pharma datasets (tenders, pricing, product lists, supplier catalogues, demand signals) to identify commercial opportunities • Build dashboards that answer strategic questions rather than simply visualise data • Produce clear recommendations and commercial narratives based on your analysis • Support customer-facing teams with insight packs demonstrating platform usage and value • Diagnose conversion bottlenecks across the commercial funnel • Identify mismatches between supply and demand and propose commercial interventions • Drive alignment between Commercial and Tech on which insights matter and why • Own and manage our BI workspace (MetaBase preferred) • Ensure dashboards are accurate, intuitive, and easy for the Commercial team to self-serve • Extract data using SQL and Python when needed (not infrastructure building) • Source and integrate new pharma-related data sources to strengthen our market understanding • Enable enterprise-level decision-making by transforming commercial, marketplace, and ecosystem data into clear, decision-ready insights for the CEO and senior leadership. • Help align teams around what matters most by translating data into prioritisation signals that inform strategy, execution focus, and resource allocation. • Serve as the bridge between Tech (data pipelines) and Commercial teams • Convert technical datasets into simple, commercially meaningful insights • Highlight trends and anomalies with clear implications for growth and strategy

• Leverage analytical and technical expertise to extract insights from complex data sets • Drive informed decision-making and strategic direction • Collaborate with cross-functional teams to identify, evaluate, and address business challenges • Employ skills in data processing, feature engineering, and data visualization to create effective solutions

• Apply knowledge of advanced analytic algorithms and technologies (e.g., machine learning, deep learning, artificial intelligence) to deliver better predictions and/or intelligent automation that enables smarter business decisions, improved customer experience, and drive productivity. • Use in-depth knowledge of the data science and AI landscape and hands-on expertise to implement solutions in production environments. • Shape advanced conceptual thinking to solve complex or novel situations that have never been dealt with before. • Select and use the appropriate statistical tests and machine learning methods to examine business hypotheses. • Create and mine datasets in Google BigQuery and other company data sources to support analyses. • Work with stakeholders in the organization to identify opportunities for leveraging analysis that drives business solutions. • Explore new technologies to enhance the Data and Analytics team’s data ecosystem. • Aid in the development of best practices used in business metrics analysis. • Support process improvement discussions with stakeholders informed by analytical insights. • Participate in business partner-facing presentations and meetings as needed. • Support a team of analysts in maintaining the data quality and governance of new and existing data sources and pipelines.

Position Summary The Senior Data Scientist is a highly skilled individual contributor responsible for leading complex analytical and modeling efforts using CAQH’s healthcare datasets. This role builds on the core Data Scientist position by taking greater ownership of analytical design, modeling decisions, and delivery of insights for high-impact initiatives. The Senior Data Scientist independently leads projects of moderate-to-high complexity, develops and validates advanced models, and works closely with engineering and business partners to translate analytical approaches into production-ready solutions. This role operates with limited oversight and is expected to apply strong technical judgment when working in ambiguous problem spaces. The Senior Data Scientist is a full-time, remote, exempt position and reports to the Sr.Director, Data Science & Analytics Specific Responsibilities - Lead the development, validation, and refinement of advanced statistical and machine learning models for complex business problems. - Serve as the primary analytical owner for assigned initiatives, with accountability for model quality, analytical rigor, and timely delivery of results. - Design analytical approaches and modeling strategies, translating business questions into well-defined technical solutions. - Perform advanced feature engineering, exploratory data analysis, and model evaluation using large, complex healthcare datasets. - Partner with Data Engineering and Information Systems teams to translate modeling approaches into production-ready solutions, while engineering teams own deployment and operations. - Support production models through performance analysis, monitoring, and retraining activities. - Design and execute experiments to test hypotheses and measure the impact of analytical solutions. - Evaluate new data sources and assess their suitability, quality, and limitations for modeling and analysis. - Communicate analytical findings, model behavior, and key assumptions to stakeholders with varying levels of technical expertise. - Document analytical methods, decisions, and results to support reproducibility and knowledge sharing. - Provide peer-level technical guidance and code review to Data Scientists and Analysts, supporting their development without formal leadership responsibility. - Contribute reusable code, features, and analytical assets to shared repositories and team standards. Skills - Advanced proficiency in Python, R, and SQL for statistical analysis, modeling, and feature engineering. - Strong hands-on experience with statistical and machine learning techniques, including regression/GLM, tree-based methods, boosting, clustering, and basic text analytics. - Proven experience developing, validating, and tuning models for real-world use cases. - Experience supporting models in production environments, including collaboration with engineers on deployment and monitoring. - Solid understanding of model evaluation, experimental design, and performance metrics. - Strong data wrangling skills and experience working with large, complex datasets. - Ability to create clear, compelling data visualizations and analytical narratives using tools such as Power BI, Tableau, or R/Shiny. - Ability to translate business problems into analytical approaches with limited guidance. - Strong written and verbal communication skills for working effectively with cross- functional stakeholders. - Experience following best practices for reproducible research, version control, and documentation. - Ability to provide constructive peer feedback and informal mentorship. - Demonstrated curiosity and willingness to learn new tools, methods, and domains. Experience - Describe the experience and attributes of the ideal candidate - 4–7 years of experience building statistical or machine learning models using large datasets - Advanced degree in Computer Science, Engineering or relevant field; PhD in Data Science or another quantitative field is preferred. Who We Are CAQH is the trusted data connector at the core of healthcare. For more than 25 years, we have powered the industry with the largest and most complete healthcare data foundation in the U.S., including more than 4.8 million provider data records sourced directly from providers and member data representing 75% of covered lives supplied by health plans. By improving how essential information flows across the system, CAQH helps healthcare operate more efficiently, accurately, and with greater confidence. What You Get At CAQH, you will do meaningful work at the intersection of healthcare, data, and technology, helping solve complex problems that make the healthcare system work better. You will collaborate with experienced professionals who care deeply about accuracy, trust, and meaningful impact in a fully remote environment. CAQH offers competitive compensation and a comprehensive benefits package for full-time employees, including medical, dental, and vision coverage, a 401(k) with company contributions and matching, paid parental leave, tuition assistance, and generous paid time off. We are committed to investing in our people and supporting professional growth over time.