Head of Data Science & ML for Risk & Fraud (Hybrid)

Trustly; New York, San Francisco (NY, CA); Hybride; USD 200 000 - 260 000; Plein temps

Avantages offerts par ce poste

Flexible PTO

Medical Insurance

401(k) match

Home office allowance

Internet stipend

Parental leave

Résumé du poste

Trustly is seeking a Director of Data Science and Machine Learning (Risk and Fraud) in the US, focused on building and deploying production ML models that determine transaction approvals and guarantees. You will lead a team of Data Scientists and ML Engineers, owning the roadmap, quality, and business impact in production.

You will mentor, hire, and develop talent while coordinating across Risk, Product, and Engineering to optimize loss, approval rates, and customer experience in Trustly’s

Qualifications

• 8+ years building and deploying ML models in production.
• At least 2 years in people leadership.
• Strong Python and SQL skills.
• Experience with fraud or payments risk domains.
• Experience in real-time inference and monitoring.
• Ability to translate model results for non-technical stakeholders.

Responsabilités

• Build, validate, deploy, and monitor ML models for risk and fraud.
• Lead a team of Data Scientists and ML Engineers, mentoring and hiring.
• Own model roadmap, performance, and production outcomes.
• Partner with Product and Engineering on scoring latency and integration.
• Present model performance and risk insights to executives.

Connaissances

Python

SQL

Fraud risk

Machine Learning

Leadership

Production ML

Formation

Bachelor's degree in quantitative field

Outils

Databricks

AWS SageMaker

Pandas

Spark

BigQuery

Snowflake

Description du poste

Trustly is seeking a Director of Data Science and Machine Learning (Risk and Fraud) in the US, focused on building and deploying production ML models that determine transaction approvals and guarantees. You will lead a team of Data Scientists and ML Engineers, owning the roadmap, quality, and business impact in production.

You will mentor, hire, and develop talent while coordinating across Risk, Product, and Engineering to optimize loss, approval rates, and customer experience in Trustly’s