Sr. Actuarial Data Scientist (Hybrid Secaucus, NJ)

Pay Range: $105k/$120k year

Salary offers are based on a wide range of factors including relevant skills training experience education and where applicable certifications obtained. Market and organizational factors are also considered. Successful candidates may be eligible to receive annual performance bonus compensation.

Benefits Information:

We are proud to offer best-in-class benefits and programs to support employees and their families in living healthy happy lives. Our pay and benefit plans have been designed to promote employee health in all respects physical financial and developmental. Depending on whether it is a part-time or full-time position some of the benefits offered may include:

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

and so much more!

The Actuarial Data Scientist provides individual contribution to the financial quantification of risk and opportunity across Quests 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 combinestrong business acumen with advanced quantitative methods and modern software engineering practicesto 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.

Actuarial Modeling Pricing and Strategic Risk Analysis

• 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 insightsas part of model development and enhancement ensuring all work aligns with relevant professional standards.

Cloud Platforms Data Engineering & MLOps for Financial Modeling

• Work with MLOps capabilities for thedeployment monitoring and lifecycle managementof financial and risk models in a cloud environment.
• Partner with enterprise data engineering to buildrobust tested analytics pipelines for end-to-end use cases (data prep modeling validation and automation).
• Champion software development best practices includingsource control coding standards and testing frameworkswithin the analytics team.

Business Partnership & Financial Strategy

• 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 apragmatic 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.

Leadership Talent Development & Delivery

• 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.

Education

• Bachelors or higher in Actuarial Science Data Science Statistics Economics Applied Mathematics or a related quantitative discipline.

Experience

• 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 environmentpartnering with business and engineering teams.
• Experience working with large complex datasets using big data technologies and script.

Technical & Quantitative Expertise

• Advanced programming proficiency with a strong preference for Pythonapplied 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-LearnGLM/GBM libraries) and a proven ability to translate model outputs into financial impacts.
• Knowledge ofMLOps model governance and production AI environments.

Leadership & Professional Skills

• 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.

Preferred Qualifications

• 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).