Director Of Applied Artificial Intelligence And Data Science

#LI-HybridOverviewThe Director of Applied AI & Data Science is a senior technical leader responsible for designing, engineering, and operationalizing production-grade AI solutions across life insurance, investments, membership, and charities. This role focuses on building scalable and reliable AI systems, including machine learning and generative AI (LLM) capabilities, within a governed enterprise data and AI ecosystem.This role provides technical leadership and oversight for the Senior Applied AI & Data Scientist, Applied AI & Data Scientist, and Senior Data & AI Solutions Architect. The Director of Applied AI & Data Science ensures solutions are production-ready, resilient, cost-effective, and aligned to responsible AI and regulatory standards.Core ResponsibilitiesDevelop and deploy advanced statistical, machine learning, and AI models supporting insurance, actuarial, claims, and investment decision-makingDesign and deliver LLM-enabled analytics and deep research solutions, including RAG-based approaches over structured and unstructured dataPerform hands-on data analysis, feature engineering, and model development using enterprise platforms (Snowflake, PostgreSQL, DB2)Define model success metrics, validation approaches, and explainability standards aligned to business and regulatory expectationsPartner with data engineers and architects to produce models, establish monitoring, and manage model lifecycle and driftApply responsible AI practices, including bias assessment, transparency, and documentation for audit and compliance reviewCommunicate analytical insights and model outcomes clearly to business leaders and technical stakeholdersCollaborate across analytics, engineering, risk, and compliance teams to ensure scalable, governed AI and analytics deliverySkills QualificationsRequired:Strong experience with Python and SQL and production system development.Experience with Snowflake and relational databases such as PostgreSQL.Experience with API development, pipelines, and system integration.Experience with monitoring, CI/CD, and operational lifecycle management of AI systems.Proven ability to lead technical teams and deliver complex solutions.Preferred:Experience in financial services or other regulated industries.Experience with DB2 or legacy-to-cloud data migration.EducationRequired:8+ years of experience in software engineering, data engineering, or ML engineering.3+ years delivering production AI/ML and/or GenAI solutions (RAG, agents, or similar)