Note: The job is a remote job and is open to candidates in USA. Quest Diagnostics' Healthcare Analytics Solutions team leverages laboratory data to develop healthcare products and services that improve outcomes across multiple markets. The Manager, Data Scientist will build, productionize, and operationalize clinical machine learning products, while partnering with clinicians, engineers, and product teams on model development, governance, deployment, and validation.
Responsibilities
- Machine learning model garden used to create predictive analytics-based data products in healthcare
- Monitoring and surveillance of state of art research in machine learning in relation to healthcare and clinical AI. Incorporating innovation as appropriate into our ML garden and solutions
- Thought leaders support for ML Ops, including 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 evidence gaining deep knowledge about advanced machine learning concepts, new model architectures as well as research-level evaluation of promising model designs and architectures
- 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
- Excellent statistics, model evaluation, and pragmatic approach to validation
- Excellent communication and problem‑solving skills; comfortable leading technical discussions with clinicians and engineers and presenting to senior executives
- Excellent scientific writing skills; we may publish studies based on novel models or methods
- A Master's degree from an accredited college or university in a related area of Data Science, Statistics, Computer Science, Mathematics, Economics, or Information Technology
- PhD preferred
- Familiarity with major commercial data platforms, including Google cloud AI solutions
- 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
- Aptitude in other programing languages like R, SAS, JavaScript
Benefits
- 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.
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