Sr. Data Scientist

NIRSense Inc. • Morrisville, NC

3d

About The Position

NIRSense is a cardiology company focused on developing world-leading non-invasive medical devices. Our tools measure oxygenation changes in the body 10x deeper than typical pulse oximetry and track the electrophysiological activity of muscles and the brain. We are a growing team of technology developers seeking candidates interested in helping advance our capabilities for a wide range of interested stakeholders who are driven to transform the way humans understand and interact with their own health.

We are seeking an experienced data scientist with expertise in statistical analysis to support clinical validation studies for our optical medical sensor products and other projects across a large research portfolio involving military, clinical, and academic collaborations. The ideal candidate will be proficient in performing sample size calculations, applying linear mixed-effects modeling, and utilizing other relevant statistical tools to ensure the robustness and accuracy of clinical data. This role will support meeting regulatory requirements to ensure our products are safe and effective for patients. This person will join a team developing and evaluating physiological monitoring wearable devices toward a definitive clinical trial in advance of regulatory submissions to the FDA, as well as relevant evaluations of those devices as their clinical utility expands. The ideal candidate possesses strong programming skills and is looking to apply these skills in the medical industry on human and animal physiological monitoring. They work well in a fast-paced and high-performance team composed of scientists and engineers.

Requirements

• Master's degree or PhD in Data Science, Biostatistics, Mathematics, or similar discipline with at least five (5) years of professional experience as a data scientist, biostatistician, or statistical analyst in the medical device, biotechnology, pharmaceutical, or clinical research industries
• Proficiency in statistical software such as GraphPad Prism, SAS, R, or SPSS; experience with specialized software for mixed-effects modeling is strongly preferred.
• Strong knowledge of advanced statistical methods, including linear mixed-effects models, survival analysis, and longitudinal data analysis.
• Hands-on experience with clinical validation studies, including design, analysis, and reporting for medical devices or diagnostics
• Familiarity with Google Colab, Jupyter, MNE, Scipy, Tensorflow, R-studio
• Strong familiarity with R packages (e.g., nlme, lme4, survival, etc.) and their applications in mixed-effects modeling and longitudinal data analysis
• Strong understanding of statistical inference, including hypothesis testing, confidence intervals, p-values, and Bayesian approaches, as applied to clinical data
• Experience with reading and interpreting relevant scientific literature
• Excellent problem-solving and troubleshooting skills
• Manage project assignments with a high degree of autonomy
• Ability to communicate complex statistical methods and results in a clear and concise manner to multidisciplinary teams

Nice To Haves

• Additional certifications or training in medical device statistics, clinical trial design, or regulatory affairs (e.g., SAS certification, FDA experience) are highly desirable
• Experience or interest in working in a hybrid work environment
• Experience in optical sensors, diagnostics, or medical device development and validation

Responsibilities

• Conduct comprehensive statistical analyses of clinical validation study data to assess product performance, safety, and efficacy
• Lead the development of statistical analysis plans and clinical trial data analysis , ensuring that study designs are statistically sound, efficient, and aligned with regulatory requirements
• Advise on selection of primary and secondary endpoints, statistical analysis methods, and key variables to include in clinical trials, to ensure that all study components, such as patient populations, inclusion/exclusion criteria, and randomization methods, are statistically justified.
• Perform rigorous sample size calculations and power analyses to determine the optimal study design and ensure studies are adequately powered to detect clinically meaningful differences
• Apply linear mixed-effects models, generalized linear models, and other advanced statistical techniques to analyze clinical trial data with complex structures (e.g., longitudinal data, hierarchical data, and repeated measures)
• Prepare, clean, and analyze existing datasets for future scientific publications, reports and presentations
• Develop and implement appropriate statistical methodologies tailored to specific study designs, including but not limited to regression analysis, survival analysis, and repeated measures analysis
• Contribute to implementing signal processing, filtering, and data conditioning approaches relevant to project deliverables
• Prepare statistical sections of clinical study reports, regulatory submission documents, and regulatory applications to support FDA clearance
• Contribute to developing, implementing, and validating novel predictive models to help inform the understanding of key clinical endpoints and outcomes
• Assist in the design and analysis of post-market surveillance studies, registries, and observational studies to gather evidence on device performance after market approval

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level