At Snorkel AI, we are pioneering new approaches to data development. We are seeking a motivated and organized Technical Program Manager (TPM): Fraud, Integrity, & Compliance to oversee program infrastructure and enablement—spanning technology, Standard Operating Procedures (SOPs), and resource management. Reporting to Expert Experience Management, this high-ownership role focuses on creating the processes, resources, and systems that drive operational efficiency, scalability, and impact, all while reducing Snorkel’s Fraud risk. We’re looking for someone who is entrepreneurial and high agency to join the early team—this person is not afraid of blank space and is eager to embrace scrappiness, experimentation, and quick iteration.

This is a full-time, 6-month fixed-term position with Snorkel AI. Assuming we find a mutual fit, there is potential for conversion to a permanent position based on business needs and individual performance. Pay Transparency Notice: Depending on your work location, the target annual salary for this position can range as detailed below. Fixed-term offers from Snorkel also include benefits (including medical, dental, vision, and 401(k)).

Pay Range: $150,000-$220,000.

Main Responsibilities

• Develop and implement technology, workflows, and SOPs that reduce fraud risks, such as identity falsification, substandard work, and plagiarism, to support Operations Managers and Associates in executing their responsibilities efficiently and autonomously.
• As a founding member of the DaaS Fraud team, balance thinking at the long-term, program level and at the short-term, tactical level. Act as the voice of Fraud prevention in decision-making.
• Perform advanced data analysis utilizing tools such as Airtable, SQL, and data visualizers to design and maintain workflows that detect and mitigate fraud risks. 
• Collaborate with engineering teams to develop or enhance fraud detection tools and systems.
• Effectively navigate tradeoffs between Fraud prevention/ Integrity/ Compliance and Growth, diplomatically managing internal relationships when those tradeoffs arise.
• Act as a connector between disparate systems (think "human-Zapier") to ensure seamless workflows and integrated fraud-prevention processes.
• Effectively navigate tradeoffs between Fraud prevention/ Integrity/ Compliance and Growth, diplomatically managing internal relationships when those tradeoffs arise.
• Partner with cross-functional teams, including Engineering, Compliance, Product Management, and Operations, to identify and address fraud vulnerabilities within operational workflows.
• Design and maintain dashboards, reporting pipelines, and monitoring tools that provide real-time insights into fraud trends, program performance, and operational efficiency, enabling proactive decision-making.
• Conduct risk assessments to identify emerging fraud threats within the business model, proposing and implementing solutions to address these risks.
• Collaborate with third-party vendors (e.g., identity verification platforms, Employers of Record) to ensure compliance with fraud prevention best practices and regulatory standards.
• Provide regular updates on fraud mitigation initiatives, program risks, and performance metrics to key stakeholders. Propose and implement corrective actions as necessary.

Minimum Qualifications

• 6+ years of experience in direct operational or technical anti-fraud experience in mitigating mass registration, e-commerce promotion abuse, or payments / chargeback scams. Similar cybersecurity experience in preventing adversarial behavior OR engaging in penetration testing and red-teaming are also acceptable. Public documentation on your projects is preferred.
• Proficiency in SQL and familiarity with tools like AirTable, Python scripting, or similar platforms. Skilled in designing queries, creating reporting pipelines, and analyzing data to identify and address fraud patterns.
• Demonstrated expertise in identifying and addressing fraud risks, including identity falsification, substandard work, and plagiarism, through both technological and procedural solutions.
• Experience with fraud detection tools, identity verification systems, or risk management technologies. Familiarity with machine learning-based fraud detection models is a strong plus.
• Bachelor’s degree in Computer Science, Data Science, or a related field. Advanced degrees or certifications (e.g., CFE, CISSP, PMP, PMI-ACP) are a plus.
• Previous experience working at a startup or similar fast-paced setting is a plus.