Senior Clinical Database Designer

Reckitt•Evansville, IN

8d•$99,000 - $149,000

About The Position

In Research and Development, we're full of highly skilled talents that include Scientists, Engineers, Medical, Clinical and Regulatory professionals - all working to create a cleaner, healthier world. With nine Centres of Excellence, we continually seek out new opportunities by using science, our entrepreneurial flare and our fearless innovation to develop and enhance our existing portfolio, never compromising on quality or performance. We do the right thing, always, by ensuring we act with responsibility and integrity, by complying with regulatory legislation across the globe, whilst ensuring our products are safe for our consumers and are to the highest quality. The size of our organisation means you'll have the opportunity to learn and work in different functions within R&D, giving you exposure to different disciplines, teams and environments. You will also have access to our Research and Development Academy, designed to develop our team and allow you to grow in our great organisation. About the role The Clinical Data & Statistical Technology Specialist designs, manages, and modernizes clinical data collection and analysis-ready data workflows for nutrition clinical studies. This role bridges Clinical Operations, Data Management, Biostatistics, Medical Science, and external partners to ensure study data are high quality, traceable, compliant, and ready for statistical analysis and reporting. The role has evolved beyond traditional clinical database design to include applied statistical support, data governance, vendor oversight, and responsible use of approved automation, AI-enabled workflows, dashboards, and analytics tools.

Requirements

Bachelor’s degree in a quantitative or health-related field (e.g., statistics, data science, clinical research) required; Master’s preferred or equivalent experience considered.
Demonstrated training or applied experience in biostatistics, statistical methods, epidemiology, or clinical data analysis.
Minimum 3 years of experience in clinical data management, database design, statistical programming support, analytics, or clinical research (healthcare/pharma preferred).
Working knowledge of clinical trial processes, including eCRF design, database build, data cleaning, endpoint collection, database lock, and study reporting.
Understanding of statistical concepts for clinical research, including data structures, analysis populations, derived variables, summaries, and quality control.
Proficiency with EDC/CDMS platforms, SQL, and at least one analytical tool (e.g., SAS, R, Python).
Familiarity with regulatory standards and practices, including ICH-GCP, data integrity, privacy/security, and SOP-driven environments.
Strong analytical, communication, and organizational skills; ability to manage multiple priorities, collaborate cross-functionally, and meet deadlines.

Nice To Haves

Task Execution Under Pressure
Makes strategic Business Decisions
Business accumen
Commercial Awareness
Objective Setting
Accountability
Consumer Insight
Creative Direction
R&D
Change Leadership
Product Lifecycle Management
Business Partnership
Collaboration and partnership building
Relationship Management
Adapt to changes in technological development plans
Ability to challenge the status quo and propose improvement
Innovation Processes
Digital transformation for R&D
Quality and Manufacturing

Responsibilities

Design and maintain clinical data systems: Translate protocols, endpoints, and statistical analysis requirements into eCRFs, database structures, edit checks, validation rules, visit schedules, data transfer specifications, and data review plans.
Support statistical analysis readiness: Partner with the Statistician to prepare, review, and validate analysis-ready data extracts, listings, descriptive summaries, reconciliation outputs, derivation logic, outlier checks, missing data checks, and other quality control outputs.
Drive data quality and compliance: Coordinate data review, discrepancy management, external data reconciliation, database lock readiness, audit-ready documentation, controlled terminology, metadata, data lineage, access, retention, and version control in alignment with ICH-GCP, data privacy, security, and SOP expectations.
Enable technology, automation, and AI: Identify and maintain approved tools, dashboards, automated checks, data quality monitoring approaches, and AI-assisted workflows that improve efficiency, consistency, scalability, and insight generation while preserving validation, documentation, human oversight, and auditability.
Manage vendors and external data flows: Provide oversight of CROs, EDC vendors, external laboratories, ePRO/eCOA providers, wearables, and other data providers to ensure data transfers, quality checks, issue resolution, and timelines are managed effectively.
Strengthen standards and knowledge continuity: Maintain and improve standards, templates, data dictionaries, validation checklists, reusable code or automation libraries, training materials, and best practices that reduce rework and support consistent study execution.