Lead Technical Program Manager, Trust & Safety

About the role

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the developm

Requirements

• Solid Python skills (e.g., Pandas, NumPy) for advanced data manipulation and scripting
• Experience working in marketplace or gig-economy platforms is a plus
• The base salary range for this full-time position in the location of San Francisco is:
• $180,800 - $226,000 USD
• PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

Benefits

Additional Information

About the Role Scale is at the frontier of GenAI and human-AI collaboration. The Gen AI Ops Trust and Safety team is focused on safeguarding human authenticity and genuineness in AI training. We are looking for a highly analytical Technical Program Manager (TPM) who leans heavily into fraud analytics and data-driven strategy to protect our ecosystem. This isn't a project management role. You will act as the lead investigative analyst and program owner for our fraud defense portfolio. Your day-to-day will involve diving deep into complex datasets to uncover hidden fraud vectors, and then translating those analytical insights into scalable rules, policies, and operational programs. By utilizing AI coding tools at high velocity, you will build out analytics pipelines, dashboards, and detection logic to shift Trust and Safety from a reactive function to a strategic one that balances safety and growth. You will: Analyze large, messy behavioral events to identify ambiguous and constantly evolving fraud patterns across the contributor lifecycle. Translate your analytical findings into actionable detection logic. You will redesign rules, optimize thresholds, and decision flows to catch bad actors while minimizing friction for high-quality contributors. Establish robust KPIs, build tracking dashboards, and define offline evaluation frameworks (e.g., false positive monitoring, precision/recall analysis) to continuously measure the health of our risk strategy. Act as the connective tissue between data, operations, and engineering. You will use your analytical findings to implement technical execution, taking new detection capabilities from data prototype to production deployment. Leverage AI-assisted IDEs daily to rapidly write complex SQL queries, automate data pulls, and streamline your analytical workflows. Connect signals, data, and operations to see the full picture. Provide clear, direct communication regarding fraud trends and strategy shifts to both technical and non-technical partners. Ideally, you'd have: 5-8 years of experience in risk strategy and fraud analytics. You have a battle-tested track record of reverse-engineering adversarial patterns, dismantling complex fraud vectors, and driving highly analytical Trust & Safety or TPM programs. Expert proficiency in SQL skills. You must be highly comfortable extracting insights from large datasets in noisy, adversarial environments. An execution-driven mindset focused on delivering measurable results, not just theoretical analysis. You are comfortable working in ambiguity and taking ownership from data problems to operational solutions. Strong proficiency with AI coding assistants to accelerate data exploration and query writing. Deep understanding of how to balance aggressive fraud detection with marketplace growth. You make decisions based on what's right for the business, not what's convenient.

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Company Intel

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