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Product Lead - Data & AI

Date Posted: Jul 7, 2026

Job #1688598
Contract
New York, New York, USA
100 - 120 per hour (USD)

Product Lead - Data & AI

Company: Confidential insurance and financial services organization backed by a leading global investment firm
Employment: Contract-to-hire; long-term contract with option/intention to convert to direct hire
Location: 5 days per week onsite in Manhattan, NY
Commitment: 40 hours/week, Monday-Friday, standard business hours
Compensation: $100-$120/hour W2, plus access to medical benefits and PTO
Reason for Opening: New role
Reports To: Head of Product, Insurance Systems
Interview Process: Hiring Manager and team members

About the Company

Our client is a highly established insurance and financial services organization focused on retirement, life insurance, annuities, reinsurance, investment solutions, and long-term financial security. The organization operates at the intersection of insurance, investments, retirement products, and enterprise technology, and is making significant investments in modern data platforms, AI-enabled capabilities, and product-centric technology teams.

Strategic Context

The insurance business provides a large, stable pool of long-duration liabilities, primarily through life insurance, annuity, retirement, and reinsurance products. The better the organization can originate insurance liabilities, understand policyholder behavior, and connect business data across the insurance platform, the more effectively it can support long-term capital deployment, risk management, profitability, and enterprise growth.

Historically, insurance organizations have operated across fragmented systems: policy administration, actuarial modeling, finance, investment accounting, asset/liability management, distribution, reinsurance, and enterprise data often sit in separate platforms. This organization is moving away from that model and building a more integrated technology ecosystem where data flows across the business through modern cloud-based architecture, embedded product teams, and a data foundation built around Snowflake, AWS, Spark, and AI-enabled capabilities.

Role Overview

The Product Lead - Data & AI will help build the data foundation underneath a long-term insurance optimization platform. The goal is to create a connected analytical environment that can evaluate how changes to pricing, crediting rates, product design, investment strategy, policyholder behavior, capital, ALM, accounting, reinsurance, and distribution affect the broader business.

For example, if the business changes the crediting rate on an annuity product, the ideal future state is to understand, as close to real time as possible, the downstream impact on sales, asset sourcing, capital, reinsurance, profitability, accounting treatment, and shareholder value.

This role sits inside the Insurance Systems organization and will work closely with embedded / forward-deployed engineers, actuarial, finance, accounting, operations, investments, distribution, and reinsurance stakeholders. The mandate is not traditional IT order-taking. The Product Lead is expected to sit close to the business, understand stakeholder workflows deeply, identify high-value opportunities proactively, and translate them into governed, scalable, and adopted data and AI products.

Key Responsibilities

  • Own the product roadmap for the organization's data and AI platform within Insurance Systems, tying technical investments to measurable business outcomes.
  • Partner with forward-deployed engineers to define reusable data products, productize data pipelines, govern AI initiatives, and ensure solutions are scalable, auditable, and aligned to business requirements.
  • Help connect historically fragmented insurance platforms across policy administration, actuarial modeling, finance, investment accounting, ALM, distribution, reinsurance, and enterprise data.
  • Translate business use cases involving pricing, crediting rates, product design, forecasting, valuation, policyholder behavior, capital, ALM, accounting, and reinsurance into clear data and AI product requirements.
  • Define and enforce data governance standards across insurance systems and data flows, including entity resolution, lineage, quality controls, access frameworks, ownership, and auditability.
  • Evaluate and recommend AI/ML tooling appropriate to the insurance context, including enterprise AI platforms, Snowflake AI capabilities, Databricks, AWS-native capabilities, and emerging insurance-specific solutions.
  • Collaborate with actuarial, finance, accounting, investments, operations, distribution, and reinsurance stakeholders to identify automation, analytics, and optimization opportunities that reduce manual workarounds.
  • Drive adoption of data and AI products by ensuring business users trust the data, understand the tools, and stop relying on shadow IT, spreadsheets, and one-off reporting processes.
  • Operate as a bridge between data engineering, AI/ML practitioners, and business users, translating technical decisions into business impact and business needs into executable engineering priorities.

Required Background

  • 5+ years in data product management, analytics product management, data platform product ownership, technical product management, or data governance, ideally within insurance, financial services, asset management, or another regulated environment.
  • Strong understanding of modern data platform concepts and architectural fluency with tools such as Snowflake, Spark/PySpark, dbt, AWS, Databricks, or comparable cloud data platforms. Engineering depth is not required, but the candidate must be able to work credibly with data engineers.
  • Experience translating complex business use cases into data product requirements, roadmap priorities, acceptance criteria, and adoption plans.
  • Experience governing AI/ML or advanced analytics initiatives in production or production-like environments, including model documentation, validation frameworks, guardrails, bias/risk controls, human review, and auditability.
  • Working knowledge of insurance or insurance-adjacent data domains such as policy, claims, underwriting, distribution, investments, actuarial, finance, accounting, ALM, capital, or reinsurance data.
  • Ability to engage senior business stakeholders and embedded engineering teams, challenge assumptions, prioritize the highest-value work, and deliver usable business outcomes quickly.
  • Experience working in agile / product-centric environments alongside data engineers, ML practitioners, architects, analysts, and business SMEs.

Preferred / Strong Plus Experience

  • Life insurance, annuities, retirement, reinsurance, or insurance investment / ALM experience.
  • Experience with policyholder behavior modeling, liability analytics, valuation, crediting-rate analysis, statutory capital, investment accounting, reinsurance structures, or multi-regime accounting.
  • Experience replacing manual workarounds, spreadsheets, shadow IT, or fragmented reporting with governed, trusted, reusable data products.
  • Prior experience in asset management, private credit, investment platforms, or insurance-linked investment strategy.
  • Familiarity with enterprise AI / data intelligence platforms such as Palantir AIP, Snowflake AI, Databricks, AWS Bedrock, or comparable tools.

What Great Looks Like

The successful Product Lead will help the organization move toward a true insurance optimization platform: a connected environment where business leaders can understand how changes in product design, pricing, crediting rates, policyholder behavior, assets, liabilities, capital, ALM, accounting, and reinsurance affect the broader enterprise.

They will be measured by whether business users trust the data, use the AI and analytics tools, stop building workarounds, and view technology as a proactive business partner rather than a service organization.

Ideal Candidate Profile

The strongest candidates will have a product mindset, technical fluency, and enough insurance or regulated financial services domain knowledge to work credibly with actuarial, finance, accounting, operations, investments, and technology stakeholders. This is not a pure engineering role and not a generic AI product role. The ideal candidate has helped turn fragmented business data and manual processes into governed, adopted, reusable data products that support better decisions in a complex enterprise environment.

About Korn Ferry

Korn Ferry unleashes potential in people, teams, and organizations. We work with our clients to design optimal organization structures, roles, and responsibilities. We help them hire the right people and advise them on how to reward and motivate their workforce while developing professionals as they navigate and advance their careers. To learn more, please visit Korn Ferry at www.Kornferry.com

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