Director of Data Science – Engineering, Fraud Platform

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of the definition, generation, quality, and utilization of data within the Identity and Financial Crime sectors.

• Create producer/consumer agreements, oversee freshness and integrity monitoring, manage lineage, dataset ownership, and source-level remediation.

• Manage fraud detection and financial-crime analytics models, including feature engineering, development, deployment, monitoring, and retraining.

• Lead a diverse team of over 25 Data Scientists, Machine Learning Engineers, and Analytics Engineers.

• Collaborate with the Engineering Manager overseeing the fraud detection platform.

• Work in partnership with the central data function on infrastructure and platform tools.

• Set data standards in conjunction with Identity engineering teams through influence and evidence-based practices.

• Build high-performing teams while ensuring a balance of delivery, reliability, and data trust.

• Recruit, retain, and nurture top-tier talent.

• Review technical work and aid in executing strategy when models fail or data integrity issues arise.

• Establish a measured baseline for data quality along the identity-to-financial-crime continuum.

• Define ownership models and dataset agreements with central data and Identity engineering leaders.

• Instrument vital data pathways for proactive monitoring.

• Evaluate model performance, degradation, retraining needs, and concentrated risk factors.

• Assess team capabilities, potential risks, and hiring requirements.

• Foster ownership, accountability, and execution.

• Lead incident response for significant fraud incidents, model failures, or data integrity issues.

• Report results to C-level executives and the board.

⛳️ Requirements

• Proven history of leading a data organization of a similar size (approximately 15–25 individuals).

• Experience in supporting the professional growth of managers and senior-level individual contributors.

• Demonstrated success in leading diverse technical teams comprising Data Scientists, Machine Learning Engineers, and Analytics Engineers.

• Strong ownership of data quality at scale, including contracts, observability, lineage, and semantic consistency.

• Proficient in contemporary lakehouse and analytics engineering practices, including Databricks or similar tools, dbt-style transformation, feature stores, real-time feature serving, and product-oriented datasets with owners and SLAs.

• Experience with production machine learning in real-time environments, including model monitoring, drift detection, and retraining pipelines.

• Proven track record with AWS at scale.

• Direct experience leading teams focused on FinCrime/Fraud or Identity engineering or data science.

• Ability to drive results from teams that are not under direct supervision.

• At least 8+ years of technical experience in a hybrid individual contributor/management role.

• Capability to attract and retain top talent and guide teams with varied skill sets.

• Experience collaborating with Engineering and Product leadership.

• Exceptional judgment and the ability to make effective trade-offs during rapid scaling.

• Prior experience leading teams in FinCrime/Fraud or Identity, with knowledge of card fraud, account takeover (ATO), first-party fraud, synthetic identity, money mule networks, regulatory contexts, and customer experience trade-offs.

• Understanding of identity verification, KYC, and onboarding data as a data domain.

• Experience partnering with Risk, Compliance, and Legal teams on regulatory responsibilities.

• Familiarity with AI, including automation, application, effectiveness of prompts, critical evaluation of AI outputs, and responsible AI utilization.

• Practical experience using AI tools.

• Experience with Claude is a nice-to-have, but not essential.

• Bonus: experience in scaling startups, data mesh or domain-oriented data ownership, stablecoins and cryptocurrencies, production AI, k8s, gRPC, Spring Boot, Java, or Python.

🏝️ Benefits

• Unlimited annual leave.

• Comprehensive healthcare benefits.

• Employee discounts.

• Flexible working environment.

• Tools for remote work.

• Team off-sites and social events.

• Professional development opportunities and support for excellence.