Data Scientist
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Job Description
Data Scientist transforming clinical, preclinical, and real-world data into evidence for Calyxo’s kidney stone medical devices. Supporting biostatistical analyses, reproducible workflows, and regulatory reporting.
Responsibilities:
- Support evidence generation across the medical device product lifecycle
- Transform real-world, clinical, and preclinical data into reliable, reproducible datasets, analyses, and insights
- Translate research and business questions into cohort definitions, data requirements, analytic plans, and deliverables
- Assess availability, provenance, quality, and suitability of real-world data, EHR records, claims data, clinical data, and other sources
- Build, validate, and maintain reproducible workflows for data extraction, transformation, cohort construction, data-quality checks, and analysis-ready datasets
- Develop, validate, and document workflows for structured clinical data and unstructured notes, including clinical concept extraction and NLP where appropriate
- Support real-world evidence and post-market analyses, including trend, subgroup, and evidence-synthesis analyses
- Provide biostatistical support for preclinical and clinical studies, including protocols, study design, endpoints, analysis populations, sample size or precision considerations, and data-collection strategies
- Support Statistical Analysis Plans, programming specifications, analysis datasets, table shells, and analysis documentation
- Review study data and structures for quality, completeness, consistency, and alignment with planned analyses; identify and coordinate issue resolution
- Perform and quality-check descriptive, inferential, interim, final, sensitivity, subgroup, and study-specific analyses
- Interpret and communicate results and contribute to study reports, clinical evaluation materials, regulatory submissions, publications, abstracts, posters, and presentations
- Build and implement secure data workflows with IT and external data partners, including access, storage, audit logging, permitted use, onboarding, and data transfer
- Maintain documentation of data definitions, source systems, transformations, statistical methods, assumptions, quality checks, and results
- Apply quality-control practices and escalate material issues and risks
- Contribute to standards, templates, workflows, and best practices for data science and biostatistical analyses
- Present analytical findings, assumptions, limitations, and recommendations to project teams and internal audiences
- Report to the Manager, Biostatistics
Requirements:
- Bachelor’s degree in data science, statistics, biostatistics, computer science, epidemiology, public health, or a related quantitative field, plus 7 years of relevant experience; or a master’s degree in a related field, plus 5 years of relevant experience
- Practical experience using R to prepare, analyze, visualize, and validate complex datasets
- Experience translating research questions into well-defined datasets, analysis plans, and transparent, reproducible analytical workflows
- Experience with statistical analysis of clinical, preclinical, observational, or other health-related data
- Working knowledge of study design, endpoint definition, analysis planning, and interpretation of clinical or preclinical study data
- Ability to develop, review, and document statistical programs and analytical outputs with appropriate quality control and traceability
- Strong data-quality, documentation, problem-solving, and communication skills
- Ability to work independently while collaborating effectively in a cross-functional team environment
- Full-time employment
- Ability to travel up to 10% of the time
- Legal authorization to work in the United States is required
- Preferred: Master’s degree or PhD in biostatistics, statistics, epidemiology, data science, or a related quantitative field
- Preferred: Familiarity with SAS, Python, and SQL
- Preferred: Experience with real-world data, EHR records, claims data, clinical trial data, or other longitudinal healthcare data
- Preferred: Familiarity with observational study methods and real-world evidence generation
- Preferred: Experience with clinical text, natural language processing, regular expressions, or clinical concept extraction
- Preferred: Experience supporting preclinical or clinical study design, statistical analysis plans, sample size or precision calculations, or statistical reporting
- Preferred: Experience creating Tables, Listings, and Figures or contributing to clinical study reports, publications, abstracts, posters, or regulatory submissions
- Preferred: Experience working in a medical-device, clinical-research, pharmaceutical, or other regulated environment
- Preferred: Familiarity with applicable clinical research and data standards, including GCP, ISO 14155, ICH E9, and relevant FDA guidance
Benefits:
- Variable incentive plan
- Stock options
- 401(k)
- Healthcare insurance
- Paid vacation
- Constant learning and dynamic challenges for professional growth
- Diverse work environment with experienced leaders
- Opportunity to shape company culture
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