Note: The job is a remote job and is open to candidates in USA. Quest Diagnostics is seeking a Manager, Data Scientist to join its Healthcare Analytics Solutions team, which develops healthcare products and services using large-scale laboratory data. The role leads the end-to-end development, validation, deployment, monitoring, and governance of clinical machine learning products while partnering with clinicians, engineers, and product teams.
Responsibilities
- End-to-end ML delivery: data curation, feature design, modelling, validation, CI/CD deployment, and monitoring
- Product ionization: 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
- Mentor and raise engineering standards across the team: coding best practices, testing, and deployment patterns
- Translate technical results into clear explanations and recommendations for technical and executive stakeholders
Skills
- 2+ years demonstrated track record delivering ML models to production (architecture, deployment, and monitoring), preferably in the healthcare industry
- 5+ years relevant experience with Python and SQL; production-grade code and testing practices
- Practical experience with model serving and monitoring, CI/CD for ML, and feature pipeline orchestration
- Experience working with healthcare data (labs, EHR, claims) and familiarity with PHI handling/HIPAA considerations
- Strong statistics, model evaluation, and pragmatic approach to validation, including the ability to articulate the bias-variance tradeoff in models to stakeholders
- Comfort with integrated generative AI tools in the model building and general coding workflow, with knowledge and strategies of both when to use and not use these tools
- Excellent communication and problem‑solving skills; comfortable leading technical discussions with clinicians and engineers and presenting to senior executives
- A bachelor's degree from an accredited college or university in a related area of Data Science, Statistics, Computer Science, Mathematics, Economics, or Information Technology
- Master's or PhD preferred
- Prior experience in regulated environments or deploying clinical decision support tools
- Demonstrated ability to leverage data visualization tools and software to present advanced analytics that are easy to interpret and spot patterns, trends, and correlations
- Experience developing, deploying, and monitoring production models in the C3.ai platform
- Excellent scientific writing skills; we may publish studies based on novel models or methods
- Experience supporting the creation of SOWs and Contracts
- Aptitude in other programing languages like R, SAS, JavaScript
Benefits
- 10% AIP target
- Fully remote, collaborative team
- Minimal travel required
- Opportunity to define production ML standards
- Clear ownership of end-to-end model lifecycle and opportunity to mentor others
Company Overview
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