Data Scientist, Machine Learning

Middesk

. Build risk & fraud ML applications: Deliver production ML models in fraud, trust & safety, KYB, and compliance domains, with measurable impact on customer workflows.

Posted 3/27/2026full-timeSan Francisco • California • 🇺🇸 United StatesSeniorLead💰 $160,000 - $230,000 per yearWebsite

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

7+ 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.

Benefits

Comp & perks

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Hard Skills & Tools

machine learningfeature engineeringclassificationgraph-based techniquesweak supervisionlarge language modelsmodel training pipelinemodel servingsignal extractionlabeling automation

Soft Skills

mentoringsetting technical directionestablishing best practices