Senior Clinical Data Research Engineer

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
• 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
• Develop documentation and methodologies for analyses and deliverables
• 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