Payments Analyst

We’re on a mission to democratize AI by building the definitive AI data development platform. The AI landscape has gone through incredible change between 2016, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!

Snorkel AI is seeking a detail-oriented Payments Analyst to own the compensation lifecycle for a broad and growing network of expert contributors who power our LLM data development efforts. You'll focus on designing and executing accurate, scalable, and transparent payment operations across complex pay structures with quality-based incentives. Your work will ensure timely, fair compensation and drive contributor satisfaction across multiple high-impact GenAI projects.

You’ll sit at the intersection of data operations, finance, product, and program teams—playing a critical role in streamlining workflows, improving reporting, and scaling compensation infrastructure. Over time, you’ll help shape pay strategy, improve automation, and elevate how we track, analyze, and optimize contributor payments. This is a fantastic opportunity for a detail-driven, technically proficient operator to join a fast-moving team at the forefront of AI data development. 

The salary range for this position based in the San Francisco Bay Area is $120,000 - $160,000. All offers include equity compensation in the form of employee stock options.

Main Responsibilities

• Own end-to-end payments processing for multiple expert-led Gen AI training data projects, including managing expert-facing communications.
• Automate, improve and maintain manual spreadsheet-based payment systems with complex and dynamic bonus structures.
• Validate data accuracy across contributor engagements by auditing inputs, extensive calculations, and bonus eligibility rules.
• Identify and implement process improvements, including automation opportunities using SQL or scripting to reduce manual operational effort.
• Collaborate with cross-functional teams such as Data Ops, Finance, Product and Engineering to troubleshoot discrepancies and streamline payroll flows.
• Design detailed contributor earnings reports and payment audit operational dashboards for both internal and external stakeholders.
• Work with operations and finance to ensure payment compliance and data traceability for accounting and tax reporting purposes.
• Use strong interpersonal and problem-solving skills to investigate and resolve contributor’s pay disputes with clarity and professionalism

Minimum Qualifications

• 3-4 years of hands-on experience in payments, payroll processing or finance with exposure to variable compensation models.
• Familiarity with compensation cycles, payment schedules, contributor invoicing, and tax compliance for gig contractors
• High attention to detail, with proven ability to manage and reconcile high volume and high complexity payments without error.
• Experience with SQL for querying, data extraction, validating, and handling large payment-related datasets
• Strong proficiency in spreadsheets, scripting/macros and reporting tools/dashboards (e.g., Looker, Tableau, Omni).
• Strong organizational and time management skills, ability to work independently and manage priorities across concurrent payment cycles and project timelines.
• Skilled at coordinating resources to manage customer support and define appropriate SLAs 
• Clear communication skills and comfort working cross-functionally with both technical and non-technical teams.
• Bachelor’s degree in Finance, Accounting, Business, Engineering, or a related field, or similar relevant work experience.

Preferred Qualifications

• Understanding of Generative AI data workflows, such as data annotation, LLM prompt design, fine-tuning, and evaluation.
• Experience working in or adjacent to ML data operations, expert networks, or human-in-the-loop systems.
• Familiarity with payment strategy design - incentive programs, quality scoring, and performance-based reward mechanisms.
• Experience improving or automating manual processes using tools such as Python, Google Script, Airtable, workflow automators.