Head of Data and AI

🕒 September 21

🇺🇸 United States – Remote

⏰ Full Time

🔴 Lead

📊 Data Scientist

👻 Ghost score 13%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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StarCompliance

WebsiteLinkedInAll Job Openings

201 - 500 employees

🏥 Healthcare

🛡️ Insurance

💼 Consulting

💰 Venture Round on 2020-12

Healthcare • Insurance • Consulting

StarCompliance is a provider of compliance solutions designed to manage and mitigate risk for companies across various industries, including financial services, pharmaceuticals, healthcare, and more. The company offers a comprehensive platform that includes solutions for managing employee conflicts of interest, personal trading, political donations, and incident management. Their platform supports compliance teams by centralizing and streamlining compliance processes with easy-to-use tools for reporting, monitoring, and analytics. StarCompliance also provides specialized services to ensure compliance with global accountability regimes, fortifying employee accountability and competency. Their solutions are cloud-ready, scalable, and provide on-demand configurability to meet the evolving regulatory requirements of a global workforce. StarCompliance is trusted by organizations around the world to uphold ethical and regulatory standards and protect company reputation.

📋 Description

• 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 they 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 • Champion pragmatic AI adoption within engineering and product development • Build, mentor, and scale a high-performing Data & AI organisation across data engineering, data science, ML engineering, and analytics • 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 • Partner with Product, Engineering, Architecture, Security, and executive teams

🎯 Requirements

• Proven delivery of production-grade AI and ML systems at scale, not just experimentation • Deep experience with generative AI and LLM-based application architectures, including fine-tuning, prompt engineering, RAG, and agentic frameworks • Strong knowledge of vector databases and semantic search, such as Pinecone, Weaviate, pgvector, or Azure AI Search • Deep background in modern data engineering, ELT/ETL patterns, and large-scale data pipeline architectures • Hands-on experience with Snowflake or an equivalent cloud data warehouse and associated data modelling patterns • Strong Azure ecosystem experience, including Azure Data Factory, Azure Synapse, Azure OpenAI Service, and Azure Machine Learning • Strong software engineering fundamentals and credibility to engage at technical depth with senior engineers • Experience with cloud-native, microservices, and event-driven architectures on Azure or an equivalent hyperscaler • Ability to make sound build-versus-buy-versus-integrate decisions across the AI and data tooling landscape • 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 and ability to connect technical investment to customer value and business outcomes • Commitment to a high standard of personal integrity and ethical conduct