Senior Clinical Data Research Engineer

The Senior Clinical Data Research Engineer will be an individual contributor in the Medical Affairs department. The role will encompass data analysis and curation from multiple large clinical datasets to inform internal reports, external presentations, manuscripts, and publications, and to inform future clinical trial design. This is a remote role. Responsibilities: Interpret clinical case reports and develop an understanding of clinical science of immune-mediated conditions, including sepsis, to inform study design and content of case report forms Support the design, interpretation, reporting, and publication of clinical studies, including detailed participation in clinical endpoint design and process, supporting EDC builds, and study execution. Perform data analysis and develop data-driven models for disease and outcome trends, value proposition, and assay clinical utility Support quality improvement activities for customers by building systems and tools for post-implementation data analysis Utilize data to track the performance and effectiveness of the IntelliSep solution in improving clinical outcomes, operational efficiency, and financial performance, and provide insights into customer-related metrics and the potential impact on patient outcomes and hospital reimbursement Collaborate with cross-functional teams to gather data and gain insights into current-state workflows and performance related to sepsis management and clinical workflows within the emergency department Appropriately apply visualization best practices and data storytelling techniques and deliver a clear and concise presentation of findings tailored to the audience Develop documentation and methodologies for analyses and deliverables Develop statistical models using clinical and biological data to inform clinical trial design Write statistical analysis plans, including statistical methodology and programming procedure Contribute analysis and graphs to educational and marketing materials, company reports, and scientific publications Qualifications: Bachelor’s degree required in biomedical engineering, bioengineering, or a related field; Master's or PhD preferred, particularly in a quantitative or life sciences discipline 5+ years of medical device related experience working with clinical data and complex diseases Proficiency in coding for data analysis using Python, including data science packages and tools (pandas, numpy, matplotlib, scikit-learn) required. Experience with SQL and relational databases required. Familiarity with AI/ML tools and large language model (LLM) applications a plus Strong analytical skills with the ability to interpret and present data effectively Experience with designing research studies and interpreting data Knowledge of statistics at the level needed for scientific publications (t-tests, survival analysis, regressions, etc.) is required; a deep background in statistics is a plus A strong desire to work in a small, fast-paced environment of a late-stage startup Candidate must be able to function as an individual contributor with minimal direct oversight A passion for understanding complex issues with a data-driven approach, experimenting, and iterating on different ways to solve a problem.