About this opportunity
StarCompliance, Inc. lists this Head of Data Science and AI - EAST COAST opportunity in northern, Kentucky. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Head of Data Science and AI – EAST COAST
About StarCompliance Are you based on the East Coast and a hands on technical Data
Are you based on the East Coast and a hands on technical Data Science AI Leader?
StarCompliance is a market-leading provider of employee compliance technology, trusted by 350+ global financial institutions and highly regulated organisations to manage regulatory obligations, monitor employee activity, and mitigate risk. Backed by private equity, we are investing in the next generation of our cloud-native, AI-enabled SaaS platform — and this role will shape the AI and data future of that platform.
Role:
We need a hands-on technical leader to own our data and AI strategy and execute it — building a high-performing Data & AI function that ships production-grade AI capabilities at scale in a heavily regulated environment.
You will partner closely with Product, Engineering, Architecture, Security, and the executive team. You will work together with the Product Director, AI & Data Products as a joint technology-and-product leadership pairing, co-owning the AI roadmap, prioritisation, and delivery outcomes.
Responsibilities:
Own the end-to-end technical strategy and execution roadmap for AI-enabled product capabilities across the StarCompliance platform.
Drive adoption of generative AI, LLM-based architectures, predictive analytics, graph intelligence, recommendation systems, and semantic search where these deliver measurable customer value.
Own the data foundation strategy, ensuring clean, trusted, well-governed data underpins every AI initiative.
Build robust MLOps capabilities, including model training pipelines, versioning, monitoring, A/B experimentation, and drift detection.
Internal AI Enablement
Champion pragmatic AI adoption within engineering and product development, accelerating how we build, not just what we build.
Leadership & Team Building
Build, mentor, and scale a high-performing Data & AI organisation across data engineering, data science, ML engineering and analytics.
Cross-Functional & Executive Collaboration
Work closely with the CTO and executive team to align AI and data initiatives with company strategy and commercial priorities.
Partner with the Product Director, AI & Data Products, co-owning the AI roadmap, prioritisation, and delivery outcomes.
Skills and Experience:
Proven delivery of production-grade AI and ML systems at scale, not just experimentation.
Deep experience with generative AI and LLM-based application architectures (fine-tuning, prompt engineering, RAG, agentic frameworks).
Strong knowledge of vector databases and semantic search (e.g. Pinecone, Weaviate, pgvector, Azure AI Search).
Deep background in modern data engineering, ELT/ETL patterns, and large-scale data pipeline architectures.
Hands-on experience with Snowflake (or equivalent cloud data warehouse) and associated data modelling patterns.
Software Engineering & Architecture
Strong software engineering fundamentals and the credibility to engage at technical depth with senior engineers.
Experience with cloud-native, microservices, and event-driven architectures on Azure (or equivalent hyperscaler).
Ability to make sound build vs buy vs integrate decisions across the AI and data tooling landscape.
Leadership & Business
Proven experience building and leading high-performing Data / AI engineering teams.
Experience within financial services, regtech, compliance, surveillance, or similarly regulated domains.
Strong commercial instincts — the ability to connect technical investment to customer value and business outcomes.
Integrity and Ethics
All StarCompliance employees are expected to commit to a high standard of personal integrity and carry out their responsibilities in an ethical manner.
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Who can apply
Review the original listing for work authorization, qualifications and employer requirements.