Job Description

Job Description

Company 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 with structured and unstructured multidimensional data, including data validation, ETL, data privacy, and advanced analytical techniques appropriate for both the data and its intended purpose. Familiarity with third-party data sources relevant to personal lines insurance exposures or the HNW market preferred.
• Experience with cloud computing platforms (e.g. AWS, Azure) and tools.
• Deep appreciation and commitment to privacy, discretion, and the elevated service standards required in HNW client engagements.
• Excellent communication, presentation, customer focus and interpersonal skills. Ability to translate complex analytics into actionable business strategies.
• Comfort with MS Office tools for interaction with partners outside the Data Science team.
• CSPA, CPCU, or similar insurance credentials preferred

Location:

This is a remote role, but we prefer candidates near NYC, Schaumburg, IL, or St. Petersburg, FL for occasional in-person collaboration and networking.

Equal Employment Opportunity Policy:

PCS values and is fully committed to diversity and inclusion. It is the policy of PCS not to discriminate against any applicant for employment, or any employee because of age, color, sex, disability, nation of origin, race, religion, sexual orientation, gender identity, or veteran status.

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