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Data Science Manager

Job in Schaumburg, Cook County, Illinois, 60159, USA
Listing for: Private Client Select
Full Time position
Listed on 2026-02-16
Job specializations:
  • IT/Tech
    Data Science Manager, Data Analyst
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Overview

About Private Client Select Insurance Services, LLC (PCS): PCS is one of the largest high net worth managing general underwriters in the market today. With a sole focus on families with $5m or more in assets, PCS provides complex insurance policies for individuals with complex needs. PCS offers property and casualty personal insurance solutions and risk management services that meet the unique and complex needs of High-Net-Worth clients.

We understand their passions and are committed to preserving the life that they have built. PCS employs approximately four hundred staff members. The company has offices in New York, NY, St. Petersburg, FL, and Schaumburg, IL. PCS has a geographically diverse workforce and supports hybrid and remote business-based flexibility.

Role Overview

We are seeking a highly strategic and detail-oriented Data Science Manager to lead the development of advanced analytics and AI solutions tailored to the unique needs of high-net-worth individuals and families. In this role, you will guide a team of data scientists to build predictive models and data-driven products that support personalized underwriting, risk mitigation, and elevated client service for complex, high-value portfolios—including fine homes, art collections, luxury vehicles, and yachts.

This is a rare opportunity to shape how data science enhances the client experience, risk selection, and underwriting profitability in a market defined by discretion, customization, and precision.

At PCS you will be challenged and encouraged to reach your greatest potential. Every day will bring new opportunities to stretch your analytical and problem-solving skills as you improve how we predict and mitigate risk and identify opportunities for greater operational efficiency.

Key Responsibilities
  • Lead, coach, and inspire a team of data scientists in the development of models and analytics to drive underwriting precision, business optimization, claims triage, and fraud detection within the high net worth (HNW) segment.
  • Translate business challenges—such as evaluating complex risk profiles or identifying risk accumulation—into data science solutions that deliver measurable value.
  • Build and maintain predictive models that support bespoke underwriting for unique assets (e.g., high-value homes, fine art, aircraft), including property loss estimation and lifestyle-based risk scoring.
  • Partner closely with underwriting, actuarial, risk engineering, and claims teams to embed AI/ML tools into the workflow, ensuring business usability and interpretability.
  • Champion the development and governance of explainable, compliant, and ethically sound models in accordance with regulatory standards and HNW client expectations.
  • Drive innovation in client segmentation, concierge service prioritization, and portfolio risk forecasting.
  • Collaborate with data engineering and IT to ensure robust data pipelines, infrastructure, and scalable MLOps practices.
  • Ensure end-to-end quality in model development, deployment, and monitoring.
  • Present strategic insights and opportunities with clarity and precision to senior leadership and cross-functional stakeholders.
Qualifications
  • B.S. in Data Science, Mathematics, Statistics, Computer Science, or related field. Advanced degree preferred.
  • 5+ years of post-college work experience in applied data science, including 2+ years in a leadership capacity.
  • Strong understanding of HNW insurance markets, including personal lines underwriting, risk selection & classification, and customer expectations. Previous experience with HNW insurance carriers or brokers, and knowledge of HNW insurance exposures, preferred.
  • Demonstrated success in building and deploying predictive models in production environments.
  • Strong analytical and problem-solving skills.
  • Ability to work productively and collaboratively with remote business partners.
  • Effective time management skills. Ability to manage long-term projects while being responsive to service needs and operational demands.
  • Expert knowledge of Python, R, SQL, and machine learning libraries. Able to adapt quickly to new technologies and to identify new opportunities they provide.
  • Advanced proficiency…
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