Sr. Actuarial Data Scientist (Hybrid - Secaucus, NJ)
About The Position
The Actuarial Data Scientist provides individual contribution to the financial quantification of risk and opportunity across Quest's strategic initiatives. This role is accountable for embedding a forward-looking, financially disciplined perspective into our advanced analytics practice by exploring and synthesizing large, complex datasets; framing hypotheses and research approaches; and building, deploying, and monitoring sophisticated statistical models in line with actuarial standards and practices. This individual will combine strong business acumen with advanced quantitative methods and modern software engineering practices to translate complex business challenges into reliable, production-ready solutions. Key applications include developing the financial architecture for value-based care initiatives, pricing at-risk contracts, and modeling the ROI of new solutions/products including AI-driven. This role is a partner to functional leaders, shaping enterprise strategy by modeling the long-term financial impact of clinical, operational, and market trends.
Requirements
- Bachelors or higher in Actuarial Science, Data Science, Statistics, Economics, Applied Mathematics, or a related quantitative discipline.
- 2 – 4+ years of progressive experience in a role requiring sophisticated forecasting and quantitative risk modeling.
- Demonstrated experience formulating, approaching, and solving complex analytical problems using a quantitative, scientific approach.
- Proven experience having deployed and monitored predictive models in a production environment, partnering with business and engineering teams.
- Experience working with large, complex datasets using big data technologies and script.
- Advanced programming proficiency with a strong preference for Python, applied to data access, scripting, statistical analysis, and system development.
- Strong experience with SQL and analytical data modeling.
- Deep understanding of long-term forecasting techniques and methods for modeling uncertainty.
- Proficiency with machine learning frameworks (e.g., Scikit-Learn, GLM/GBM libraries) and a proven ability to translate model outputs into financial impacts.
- Knowledge of MLOps, model governance, and production AI environments.
- Excellent communication skills with the ability to influence senior leaders by articulating the "so what" behind complex models.
- Proven ability to deliver outcomes in a complex, matrixed organization.
Nice To Haves
- Credentialed Actuary (ASA, FSA) or significant progress toward credentials.
- Advanced degrees with a focus on a quantitative, economics, or health-related field.
- Prior experience in healthcare, diagnostics, insurance, or life sciences.
- Direct experience designing or operating analytics and AI solutions on Google Cloud Platform (GCP).
Responsibilities
- Design, development, and deployment of sophisticated financial and risk models to evaluate the profitability and risk profile of key business initiatives.
- Develop dynamic pricing and underwriting frameworks for a range of commercial applications, including value-based care and at-risk partnerships, using advanced mathematical and statistical techniques (e.g., GLM/GBM).
- Build complex, tested programs to run statistical tests on data, discover insights and relationships, and understand complex relationships across attributes.
- Apply stochastic modeling to forecast healthcare cost and utilization, translating these insights into actionable business strategies and applying reserving concepts (e.g., IBNR) and stress testing to financial plans.
- Incorporate findings and provide industry and competitor insights as part of model development and enhancement, ensuring all work aligns with relevant professional standards.
- Work with MLOps capabilities for the deployment, monitoring, and lifecycle management of financial and risk models in a cloud environment.
- Partner with enterprise data engineering to build robust, tested analytics pipelines for end-to-end use cases (data prep, modeling, validation, and automation).
- Champion software development best practices including source control, coding standards, and testing frameworks within the analytics team.
- Serve as a strategic partner to senior business leaders, translating complex models into clear financial implications and actionable recommendations.
- Quantify and communicate the potential ROI and risk drivers of major analytics initiatives, demonstrating a pragmatic approach to solution-selection and an understanding of when a non-AI approach is optimal.
- Enhance traditional financial planning and analysis (FP&A) with more dynamic, probabilistic forecasting methods.
- Lead, mentor, and develop data scientists and analysts, instilling a culture of financial discipline, risk awareness, and technical excellence.
- Establish and reinforce best practices for the entire model lifecycle, from hypothesis generation to production monitoring.
Benefits
- Day 1 Medical, supplemental health, dental & vision for FT employees who work 30+ hours
- Best-in-class well-being programs
- Annual, no-cost health assessment program Blueprint for Wellness®
- healthyMINDS mental health program
- Vacation and Health/Flex Time
- 6 Holidays plus 1 "MyDay" off
- FinFit financial coaching and services
- 401(k) pre-tax and/or Roth IRA with company match up to 5% after 12 months of service
- Employee stock purchase plan
- Life and disability insurance, plus buy-up option
- Flexible Spending Accounts
- Annual incentive plans
- Matching gifts program
- Education assistance through MyQuest for Education
- Career advancement opportunities
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
