• Design, monitor and measure complex A/B tests and experiments to validate business hypotheses, ensuring the statistical robustness of decisions. • Create sales performance metrics for products and develop solutions that improve portfolio profitability. • Develop descriptive and predictive data science solutions focused on process optimization, resource allocation and decision support for health and portfolio performance areas. • Execute all stages of the data science solution lifecycle: business understanding, variable study and preparation, mathematical/statistical modeling, performance validation, support for model deployment to production and measurement of results. • Collaborate with the functional area on the design, use and monitoring of models.

Role Description ClinChoice is searching for a Principal Clinical Data Scientist Consultant – R Programmer to join one of our clients. We are seeking a Principal Clinical Data Scientist to join our Scientific Computing Technology group, which builds the open-source tools, R packages, SAS macros, and computing systems that power clinical programming, data management, and biostatistics across the organization. Reporting to the Director of Statistical Programming, this role blends hands-on clinical deliverables with contributions to the open-source and internal tooling that supports the wider clinical technical community. The ideal candidate has strong R skills, deep clinical programming experience, working Python familiarity, and an interest in modern, reproducible workflows. This position is open to remote candidates. Key Responsibilities - Develop, validate, and maintain SDTM and ADaM datasets in R — using admiral and the broader pharmaverse — following CDISC standards. - Generate Tables, Listings, and Figures (TLFs) in R or SAS as required by study needs. - Perform Pinnacle21 validation, resolve findings, and refine specifications to ensure CDISC compliance and submission readiness. - Write efficient, reproducible, well-structured R code for clinical data analysis and reporting. - Contribute to open-source and internal tooling — including R Shiny / teal modules, R packages, SAS macros, and Python utilities — used by clinical programming, data management, and biostatistics teams. - Partner with statisticians, data managers, and clinical teams to translate programming requirements into reliable deliverables. - Perform QC, reconcile data issues, and ensure outputs meet regulatory expectations (e.g., FDA, EMA). - Support automation, pipeline development, and version-controlled workflows. - Use SAS for legacy studies or where SAS support is needed. Qualifications - Bachelor’s or Master’s degree in Statistics, Computer Science, Mathematics, Life Sciences, or a related field. - 5+ years in clinical programming, with a strong focus on R. - Proven experience producing SDTM and ADaM datasets in R, including hands-on use of admiral. - Experience with Pinnacle21 validation and remediation. - Working knowledge of SAS programming. - Working knowledge of Python for analytics, scripting, or tooling. - Solid understanding of CDISC standards (SDTM, ADaM) and metadata-driven programming. - Experience with clinical trial data, regulatory submissions, and QC processes. - Strong analytical, problem-solving, and documentation skills. Preferred Qualifications - Broader pharmaverse experience (e.g., tidyCDISC, rtables) and tidyverse fluency. - Experience building or contributing to R Shiny apps, teal modules, or R packages used by other teams. - Exposure to AI/ML tooling in a clinical or programming context. - Real-World Evidence (RWE) experience — e.g., mapping Flatiron or claims/EHR data into CDISC-aligned structures. - R Markdown, Quarto, or other reproducible reporting workflows. - GxP validation, Git-based version control, and CI/CD or automated workflows. - CRO or pharmaceutical industry experience. The Application Process Once you have submitted your CV, you will receive an acknowledgement that we have received it. If you have the requirements we need, you will be invited for a phone interview as the first step. Unfortunately, due to the number of applications we receive, we cannot reply to everyone individually if you are not successful.

• Own data management study deliverables end-to-end — from data capture tool development through database lock • Partner closely with CROs and third-party vendors to keep clinical data accurate, timely, and audit-ready • Represent DM as the functional lead at study team meetings; responsible for communication and collaboration • Assumes ownership for DM study deliverables within DM scope of services including overseeing overall quality • Data Reconciliation including coordination of transfers and issue resolution with other functional areas • Investigation and remediation of reviewer-reported data issues • Coordinates with ProKidney, CRO and other 3rd party vendors to develop and maintain DM startup timelines • Responsible for submitting queries in the EDC and with the central laboratory • Ensure quality check of clinical data as appropriate for statistical review, interim review, and final database lock • Responsible for database lock, close-out audit and archiving activities • Manage and store data transfers from 3rd party vendors • Development and management of patient profiles for clinical review and data cleaning

• Own product strategy, roadmap, and execution for a clinical data domain spanning the full care continuum • Lead end-to-end product development, from discovery through delivery, across cross-functional teams including data science, data engineering, and software engineering • Translate clinical and claims data into actionable analytics, including transitions of care analysis, patient outcomes, performance benchmarking, referral patterns, cost, and network leakage • Identify and integrate AI/ML-driven capabilities (e.g., predictive analytics, risk stratification, anomaly detection) to enhance clinical insights and drive smarter decision-making for value-based care and post-acute providers • Build and ship AI-powered product features, from concept through adoption, including generative AI, predictive models, and intelligent automation embedded directly into clinical and operational workflows for users • Use AI tools daily across the full product lifecycle, including discovery, prototyping, requirements definition, stakeholder communication, and GTM enablement • Drive measurable business outcomes including ARR growth, customer retention, and NPS, ensuring product investments deliver impact • Own the clinical narrative around care transitions, including discharge planning, referral patterns, and cross-setting patient flow, translating those workflows into product requirements • Independently prioritize and manage the product backlog, balancing clinical user needs, business value, and technical investment • Collaborate with GTM teams (Sales, Marketing, Customer Success) to support positioning, enablement, and successful product launches • Conduct market and competitive analysis to inform product direction and identify opportunities for clinical and AI-driven innovation • Champion a product-led mindset, driving clarity, accountability, and continuous improvement across teams