About the position Healthcare Analytics Solutions (HAS) is an innovative team within Quest Diagnostics that leverages Quest data to develop products and services to improve outcomes in healthcare across many different markets (Pharma, Clinical Trials, Health Plans/Payers, Hospitals/Health Systems, and Public Health agencies). Join HAS to build, productionize, and operationalize clinical ML products using billions of results from Quest laboratory data. You will partner with clinicians, engineers, and product teams to deliver robust, compliant, and well‑documented models that impact patient care and downstream products. Fully remote, minimal travel required; strong emphasis on hands‑on production experience and pragmatic problem solving.

Responsibilities

• End-to-end ML delivery: data curation, feature design, modelling, validation, CI/CD deployment, and monitoring.
• Productionization: containerization, model serving, performance tuning, rollout strategies, and observability (drift, performance, alerts).
• Model governance: reproducibility, versioning, bias/fairness checks, and audit-ready documentation.
• Integration of advanced analytics and machine learning models into business products and services including business intelligence dashboards and real-time analytics.
• Curation of data sets from Quest and non-Quest data sources in support of deriving business insights driven by advanced analytics.
• Cross-functional partnership with clinicians and product owners to define outcomes, acceptance criteria, and validation plans.
• Other duties as assigned

Requirements

• Master’s degree or PhD student in quantitative field including Data Science, Biostatistics, Bioinformatics, Public Health, Computer Science, Economics, Statistics, or Mathematics
• Strong ability to work on multiple projects simultaneously, balancing priorities, and to work on cross-functional teams
• Ability to work on large data sets using Python is required

Nice-to-haves

• Candidates with both advanced Python and SQL skills are strongly preferred
• Demonstrated track record delivering ML models to production (architecture, deployment, and monitoring), preferably in the healthcare industry, is strongly preferred
• Experience using data mining, pattern recognition, machine learning, deep learning, statistical and/or mathematical programming and modeling preferred
• Use of tools like AWS-Sagemaker, Vertex AI, or C3.ai preferred
• Professional data science/data engineering experience preferred
• Experience with clinical/health care data and specifically lab data preferred
• Excellent communication skills strongly preferred
• Open to limited travel