Director, Data and Analytics – AI Engineering

🕒 Setembro 28

🦌 Connecticut, Illinois, +1 estados a mais – Remoto

🦌 Connecticut – Remote 🌽 Illinois – Remote 🌲 North Carolina – Remote

💵 $156.000 - $234.000 / ano

⏰ Tempo Integral

🔴 Especialista

🤖 Engenheiro de IA

🦅 Patrocina Visto H1B

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The Hartford

SiteLinkedInTodas as Vagas

10.000+ funcionários

Fundada em 1810

🛡️ Seguros

💸 Finanças

👥 B2C

Insurance • Finance • B2C

A The Hartford é uma empresa de seguros bem estabelecida que oferece uma variedade de produtos, incluindo seguros de automóveis, residências e empresariais. Com mais de 200 anos de experiência, atende tanto a indivíduos quanto a pequenas e médias empresas, proporcionando soluções de seguros sob medida e benefícios para funcionários. A empresa é particularmente conhecida por seus programas de seguro de automóveis e residências endossados pela AARP, que oferecem benefícios e descontos exclusivos para membros.

Descrição

• Lead execution of a complex and large Data and Analytics portfolio • Develop and implement a strategic roadmap to modernize legacy data and analytics ecosystems using Cloud and AI • Enable data domains and data products for reporting, data science, AI/ML, and analytics stakeholders • Ensure data architecture and solutions align with enterprise-wide Data, AI, and Analytics standards • Communicate strategy, execution progress, and outcomes to diverse stakeholders through thought leadership and presentations • Implement AI data pipelines integrating structured, semi-structured, and unstructured data for AI and Agentic solutions • Establish standardized AI data engineering processes and ensure data quality and compliance • Oversee design, development, and maintenance of data pipelines, warehouses, lakes, and reporting systems • Build, mentor, and lead a high-performing team of business data analysts, data engineers, and release train engineers • Champion developer productivity improvements across the data management lifecycle • Research and implement AI-driven pipeline generation, DevOps practices, and automated data quality frameworks • Evaluate emerging data engineering and AI/ML technologies, design prototypes, conduct experiments, and recommend tools • Define and implement data management frameworks for Enterprise Data Governance and Data Quality • Manage the portfolio budget and financials • Partner with Technology, Data, AI Platform, ML Ops, and Architecture teams to influence strategy and tooling • Translate actuarial needs into scalable Snowflake data products and AI-enabled analytics solutions

🎯 Requisitos

• 8-10 years of experience in data engineering, analytics solution delivery, actuarial analytics, or related data-intensive roles • 3+ years' experience supporting actuarial, insurance, pricing, reserving, modeling, underwriting, portfolio management, or financial analytics use cases • Mastery level data engineering and architecture skills • Deep expertise in data architecture patterns, data warehouses, data integration, data lakes, data domains, data products, business intelligence, cloud technology capabilities, and data governance • Technical expertise in LLMs, AI platforms, prompt engineering, LLM optimization, RAG architectures, and vector database technologies • Experience enabling AI for analytics use cases, including analytic agents, natural language analytics, governed knowledge bases, forecasting, monitoring, deep-dive analysis, and decision-support solutions for actuaries • Ability to design, implement, and oversee Snowflake-based data pipelines, transformations, validations, and analytic consumption patterns • Proven experience building modern actuarial data products, governed consumption layers, semantic layers, reusable metrics, data quality controls, and analytics-ready models • Proven ability to use Snowflake-native and cloud-integrated capabilities for actuarial workflows, predictive model outputs, monitoring, dashboards, and AI-enabled analytics solutions • Ability to promote exploratory actuarial solutions into sustainable, production-ready assets with ownership, monitoring, documentation, and support expectations • Strong understanding of actuarial measures and analytical concepts such as loss ratio, frequency, severity, rate adequacy, modeled indications, emergence monitoring, renewal health, and book assessment preferred • Ability to partner with actuaries, data scientists, analytics teams, engineering teams, and business stakeholders • Experience with Agile at Scale and iterative development through cross-functional teams

🏖️ Benefícios

• Short-term or annual bonuses • Long-term incentives • On-the-spot recognition • Hybrid work schedule or remote arrangement • Perks & Benefits