Data Scientist, Middesk

• Ideally you have shipped external-facing models in the risk/fraud space and know the messy realities of imbalanced data, low labels, and changing behavior
• 5+ years applied ML experience, with direct impact in risk, fraud, trust & safety, compliance, or adjacent high-stakes domains
• Proven track record of shipping ML models from research to production in external-facing products
• Expertise in classification with real-world challenges, for example: imbalanced labels, sparse signals, cold start, and production version management
• Hands-on ML infrastructure experience: feature stores, model management, ML training/serving pipelines
• Comfort as a senior IC: setting technical direction, mentoring peers, and establishing best practices

Desirable

• We are actively building AI-driven applications that streamline customer workflows, focusing on business onboarding
• With our proprietary identity data assets and deep domain expertise, we are uniquely positioned to expand into a broader set of AI-powered solutions that drive long-term growth
• We’re looking for a hands-on applied ML expert to help build the technical foundation for these efforts
• This is a highly technical, hands-on role with wide influence on how we design, build, and scale ML at Middesk
• Build risk & fraud ML applications: Deliver production ML models in fraud, trust & safety, KYB, and compliance domains, with measurable impact on customer workflows
• Tackle hard data problems: Work on classification problems with extreme class imbalance, sparse signals, and “cold start” label challenges
• Innovate in feature engineering & labeling: Use graph-based techniques, weak supervision, LLMs, and AI agents to improve signal extraction and automate labeling process
• Establish ML infrastructure foundations: Partner with platform engineering team to design feature services, model training pipeline, model serving standards, and orchestration to scale multiple ML use cases