Principal Technical Product Manager

Dir Data Science - GD06AE

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Principal Technical Product Manager (AI & Data Science)

Role Overview

We are seeking aPrincipal Technical Product Manager to lead the strategy, development, and scaling of enterprise AI and data science products. This role sits at the intersection ofproduct strategy, advanced analytics, and platform engineering, driving the end-to-end lifecycle from concept through production.

As a senior individual contributor, you will operate as aproduct leader and technical translator, aligning stakeholders, shaping roadmaps, and ensuring delivery of high-impact AI solutions that deliver measurable business value.

Key Responsibilities

Product Strategy & Vision

• Define and own theproduct vision, strategy, and roadmap for AI/ML-driven products and data platforms
• Translate business objectives intoscalable, reusable AI product capabilities
• Identify opportunities to leverageadvanced analytics, machine learning, and generative AI to drive business impact

End-to-End Product Ownership

• Lead product lifecycle fromopportunity identification → POC → MVP → production scaling
• Ensure products meetenterprise standards for architecture, governance, and compliance
• Define success metrics (KPIs, adoption, ROI) and manage performance post-launch

Technical Product Leadership

• Partner closely with engineering, data science, and platform teams to:
  • Definetechnical requirements and architecture trade-offs
  • Prioritize backlog and align delivery to business value
  • Ensure solutions arescalable, secure, and production-ready
• Stay current on AI/ML trends and evaluate emerging technologies

Stakeholder & Cross-Functional Alignment

• Act as primary interface acrossbusiness, technology, data science, and governance teams
• Lead workshops and facilitate alignment on priorities, scope, and trade-offs
• Communicate clearly with bothexecutive and technical audiences

Execution & Delivery Excellence

• Driveagile product development, including backlog prioritization and sprint planning
• Manage dependencies across teams and ensureon-time, high-quality delivery
• Proactively identify risks and implement mitigation strategies

Governance, Risk, and Responsible AI

• Ensure solutions adhere toenterprise AI governance, security, and compliance standards
• Embed best practices formodel validation, monitoring, explainability, and fairness
• Partner with risk, legal, and security teams on production readiness

Qualifications

Experience

• 10+ years of product management experience, including:
  • 10+ years intechnical product management
  • Proven experience deliveringdata science, AI/ML, or analytics products
• Track record of shipping products from concept to production at scale
• Advanced understanding of adoption strategies and metrics

Technical Skills

• Strong understanding of:
  • Machine learning lifecycle (data prep, modeling, deployment, monitoring)
  • Data platforms (cloud, data pipelines, APIs, analytics tools)
  • AI/GenAI concepts (LLMs, prompt engineering, evaluation frameworks)
• Ability to engage deeply in technical conversations with engineers and data scientists

Leadership & Execution

• Demonstrated ability to leadcross-functional, matrixed teams
• Strong prioritization and decision-making skills in ambiguous environments
• Excellent communication and stakeholder management skills

Education

• Master’s degree in Computer Science, Engineering, Data Science, or related field (or equivalent experience)

Preferred Qualifications

• Experience buildingenterprise AI platforms or AI-enabled products, specifically in Gemini Enterprise Agent Platform
• Familiarity withcloud environments (GCP, AWS, Azure) and modern data stacks
• Experience withregulated industries (insurance, finance, healthcare)

Key Skills for Regulated Industries:

• Regulatory & Compliance Acumen
  • Deep understanding of regulatory frameworks (e.g., SOX, GDPR, HIPAA, Model Risk Management)
  • Ability to translate regulatory requirements intoproduct features, controls, and workflows
• Responsible AI & Model Governance
  • Experience implementingmodel validation, explainability, fairness, and bias detection
  • Familiarity withAI governance frameworks, auditability, and documentation standards
  • Ability to operationalizemodel risk management (MRM) practices across the product lifecycle
• Data Privacy & Security
  • Strong understanding ofdata protection, PII handling, and data classification
  • Experience partnering with security teams onaccess controls, encryption, and data lineage
  • Knowledge ofsecure AI/ML architectures (e.g., VPC controls, air-gapped environments)
• Audit & Traceability
  • Ability to ensure solutions arefully auditable, with clear lineage from data → model → output
  • Experience supportinginternal/external audits with appropriate controls and documentation
• Enterprise Risk Management
  • Ability to identify and manageoperational, reputational, and compliance risks
  • Experience working with Legal, Risk, and Compliance functions toapprove and scale AI solutions
• Policy-to-Product Translation
  • Proven ability to takeambiguous regulatory or governance requirements and translate them into:
    • Product requirements
    • Acceptance criteria
    • Monitoring and reporting capabilities
• Change Management & Adoption in Regulated Environments
  • Experience driving adoption whererisk sensitivity is high and approvals are multi-layered
  • Ability to balanceinnovation speed with control rigor

Compensation

The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:

$153,200 - $229,800

Equal OpportunityEmployer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity orExpression/Religion/Age

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