Prenosis Inc. is an artificial intelligence company pioneering precision medicine in acute care. The company is looking to build AI-powered solutions that help clinicians match the right treatment to the right patient at the right time, by analyzing complex biological and clinical signals to stratify patients, predict outcomes, and guide therapeutic decisions in emergency departments and ICUs.
Requirements
- Demonstrated experience applying machine learning and statistical methods to clinical, genomic, or healthcare datasets
- Expert-level proficiency in Python and/or R, with strong software engineering practices (version control, testing, documentation)
- Hands-on experience with clinical trial design, regulatory requirements (FDA/EMA), and healthcare data standards (HL7, FHIR, OMOP)
- Experience with cloud computing platforms (AWS, GCP, Azure) and scalable ML infrastructure
- Familiarity with model interpretability techniques (SHAP, LIME) for regulatory and clinical transparency
- Strong critical thinking skills with ability to formulate and test hypotheses independently
Responsibilities
- Develop and deploy machine learning models and predictive algorithms to extract actionable insights from complex patient clinical data for personalized medicine applications
- Design, implement, and optimize end-to-end data science pipelines leveraging Prenosis's proprietary datasets with diverse clinical, molecular, and real-world evidence features
- Conduct exploratory data analysis and feature engineering initiatives to identify novel biomarkers and patient stratification strategies
- Translate complex analytical findings into clear, compelling narratives and visualizations for diverse stakeholders including clinical teams, regulatory bodies, and commercial partners
- Validate model performance and ensure reproducibility in accordance with regulatory standards and good machine learning practices
- Collaborate with cross-functional teams (clinical operations, medical affairs, product development) to define analytical strategies that address critical business and clinical questions
- Contribute to the technical development of regulatory submissions, grant applications, peer-reviewed publications, and intellectual property filings
Other
- PhD in Computer Science, Biostatistics, Statistics, Computational Biology, Bioinformatics, or related quantitative field; OR Master's degree with 4+ years of industry experience in pharmaceutical/clinical research settings
- Proven track record of translating analytical insights into clinical or business impact
- Excellent communication skills with experience presenting technical content to non-technical audiences
- Approximately 5% time including biannual 3-4 day all-hands meetings
- Must be eligible to work in the US without sponsorship
