Director, Compliance Data Science & AI

OKX•San Jose, CA

23h•Hybrid

About The Position

Few compliance analytics roles offer this combination: genuinely novel problems, global scale, and the freedom to build rather than maintain. At a global crypto exchange, the financial crime data landscape is more varied, more real-time, and more analytically rich than almost anywhere in traditional finance. The regulatory environment is evolving quickly, the typologies are new territory, and the analytical work has direct impact on how the organisation detects and responds to financial crime. This role sits within the Product organisation and is dedicated entirely to that space, covering AML, sanctions, KYC/KYB, transaction monitoring, and beyond. You will join a collaborative team of data scientists, data engineers, and business analysts, working closely with compliance stakeholders across the full range of financial crime domains. The role sits at the point where product engineering culture meets compliance depth, and you will have room to contribute across both. It is a role well suited to someone who enjoys varied, substantive work and values being part of a team that takes the quality of its output seriously. The team is actively building toward an AI-native way of working. LLM-assisted coding, automated analytical pipelines, and AI-augmented investigation tools are already part of how the team operates or in active development. For someone who has wanted to apply AI seriously in a compliance context without cutting corners on rigour or auditability, this is an environment where that work is already underway and genuinely valued.

Requirements

10+ years in data science, quantitative analytics, or ML, with meaningful time in a leadership or senior individual contributor capacity in a compliance or regulatory analytics environment within financial services, fintech, or a crypto exchange. We welcome candidates across varied seniority levels; scope and responsibilities will be calibrated to your experience.
Solid compliance domain knowledge, with hands-on experience across one or more of AML typology detection, sanctions analytics, KYC/KYB modelling, customer risk rating, or transaction monitoring. Comfort navigating nuanced conversations with compliance stakeholders, where analytical and regulatory requirements do not always align neatly, will serve you well in this role.
Strong Python and SQL, applied ML across supervised, unsupervised, anomaly detection, and graph-based methods, and enough MLOps and data engineering fluency to engage credibly in production design conversations with engineers.
A working AI-first mindset: you use AI tools regularly in your own work, have a view on where LLMs and automation genuinely improve compliance analytics workflows, and understand where they introduce risk. Experience helping a team build confidence with new AI approaches is a plus.
Good cross-functional communication skills, with the ability to engage clearly with compliance officers, product managers, and engineers who each bring different priorities to the same conversation.
Experience mentoring data scientists and analysts, with a genuine interest in helping colleagues develop and in raising the overall quality of the work around you.
Familiarity with model governance, explainability requirements, and the documentation standards associated with analytics work in a regulated environment.
Some exposure to working within or alongside a Product organisation, with an understanding of how delivery cycles, engineering prioritisation, and roadmaps are managed in practice.
Familiarity with the crypto ecosystem, on-chain analytics, blockchain data, or VASP compliance frameworks is a meaningful advantage for this role.
Experience with regulatory examinations, enforcement responses, or formal model validation in a compliance context. Having worked through one of those processes gives you a perspective on what the work ultimately needs to withstand, and that experience is genuinely valued here.

Responsibilities

Lead delivery of advanced analytics and AI initiatives across core compliance domains including AML detection, sanctions screening, KYC/KYB risk modelling, customer risk rating, transaction monitoring calibration, and SAR analytics, with involvement from problem definition through to production.
Work as the primary point of contact between the Product engineering team and compliance stakeholders, translating regulatory requirements into scoped analytical workstreams and bringing analytical findings back to compliance teams in a form that is clear, actionable, and well grounded in the underlying data.
Drive the adoption of AI-assisted workflows across the team's compliance analytics work: LLM-assisted coding, automated analytical pipelines, AI-augmented investigation and triage. You will help demonstrate what AI-native working looks like in a compliance context and support the broader team in building confidence with these approaches.
Work hands-on with ML engineers on detection models and risk scoring systems that are production-grade and auditable. Compliance analytics requires both explainability and reliability, and experience balancing those two requirements in practice will be important here.
Provide technical guidance and mentorship to data scientists and analytics engineers through code and methodology reviews, collaborative problem solving on complex compliance workstreams, and a consistent focus on raising the quality of the work across the team.
Partner with product managers on scoping, sequencing, and effort estimation for compliance analytics initiatives, bringing both technical and regulatory context to delivery planning conversations.
Maintain documentation and governance standards for compliance analytics output, ensuring that models and analyses are recorded clearly enough to support internal review, regulatory scrutiny, and knowledge continuity within the team.
Contribute to regulatory responses and internal audit events by leading the data science workstream: coordinating analytical evidence, supporting the technical narrative, and presenting findings to compliance and legal review functions where required.