Head of Data Science and AI - EAST COAST

Starcompliance; Gisborne; On-site; NZD 180,000 - 240,000; Full time

Job summary

StarCompliance seeks a hands-on Data & AI leader to own the data and AI strategy and ship production-grade AI capabilities at scale in a heavily regulated environment.

You will partner with Product, Engineering and executives to co-own the AI roadmap and delivery outcomes, while mentoring a growing Data & AI team across data engineering, data science, ML engineering and analytics.

Qualifications

• Proven delivery of production-grade AI/ML systems at scale.
• Experience with generative AI and LLM-based architectures (fine-tuning, prompt engineering).
• Strong knowledge of vector databases and semantic search.

Responsibilities

• Own end-to-end technical strategy and execution roadmap for AI-enabled product capabilities.
• Drive adoption of generative AI, LLMs, analytics and related architectures.
• Build and lead a high-performing Data & AI organisation across data engineering, data science, ML engineering and analytics.
• Collaborate with CTO and executive team to align AI initiatives with business strategy.

Skills

AI strategy

Data engineering

ML engineering

LLM architectures

MLOps

Azure ecosystem

Snowflake

Vector databases

Semantic search

Leadership

Tools

Snowflake

Azure Data Factory

Azure Synapse

Azure OpenAI Service

Azure Machine Learning

Weaviate

Pinecone

Job description

About StarCompliance

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.

AI Product Delivery & Strategy

• 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.

Data Platform & Engineering

• 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.

AI & Machine Learning

• 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).

Data Engineering & Platforms

• 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.
• Strong Azure ecosystem experience: Azure Data Factory, Azure Synapse, Azure OpenAI Service, and Azure Machine Learning.

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.

All StarCompliance employees are expected to commit to a high standard of personal integrity and carry out their responsibilities in an ethical manner.