S

Snorkel AI

Builds training data and test environments for AI

Finance Manager - Data as a Service

Corporate Finance & FP&AConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA$130k - $180k

About the Job

Requirements

  • 5–8 years of experience in FP&A, product or business finance, deal desk, or strategic finance, including at least 2 years at a high-growth technology company.
  • Hands-on ownership of a revenue forecast and a unit-economics or pricing model.
  • Fluency in gross margin versus contribution margin, cost-to-serve, and how pricing, discounting, and incentives affect both.
  • Experience with services or labor-based delivery economics, including utilization, headcount per project, and contractor mix.
  • Expert spreadsheet modeling in Google Sheets or Excel and working SQL skills; ability to pull data from a CRM and data warehouse.
  • Ability to write concise executive summaries that leadership can act on.
  • Ability to make reasoned decisions with incomplete data, state assumptions, and refine them as more facts become available.
  • A process-improvement mindset, including identifying friction, proposing simpler approaches, and driving adoption.
  • Bachelor's degree in finance, economics, engineering, or a related field.

Responsibilities

  • Maintain the DaaS revenue model, including bookings, acceptance-based revenue, and ARR by deal, with scenario cases for planning.
  • Partner with RevOps on the weekly revenue and ARR forecast, and produce the weekly forecast deck and leadership summary.
  • Reconcile the field's commit, forecast, and best-case views with deal-by-deal finance analysis; quantify coverage, swing deals, and risks.
  • Track delivery pacing and acceptance against plan and identify execution risks.
  • Build forecast-versus-actual and bookings-to-revenue bridges and variance analyses for quarterly and annual planning.
  • Build DaaS inputs to the annual operating plan and long-range plan for revenue, cost of delivery, margin, and delivery headcount, including monthly actual-versus-plan variance analysis.
  • Partner with Accounting on revenue recognition inputs, cost of goods sold, and margin actuals.
  • Run and maintain the delivery capacity model with Delivery Ops, covering utilization, project mix, headcount per project, and cost to deliver.
  • Reconcile the capacity plan with actual staffing data and explain variances in mix, productivity, and headcount.
  • Translate the bookings pipeline into staffing demand and flag hiring or Expert Contributor needs ahead of the quarter.
  • Lead regular capacity planning reviews with Delivery leadership.
  • Surface trends in pricing, mix, margin, and pacing with clear recommendations for leadership.
  • Partner with Deal Desk on finance input for deals; review deal models and pricing templates for accuracy and margin, and recommend adjustments.
  • Analyze customer and product profitability by tying cost to deliver to revenue.
  • Assess the economics required for each product to meet margin targets and identify where to invest next.
  • Identify broken or slow processes and recommend and drive fixes that shorten cycle time and improve data quality.
  • Automate recurring models by moving them from manual spreadsheets toward scalable, auditable tools.
  • Support board and investor content for the DaaS business.

Desired Qualifications

  • Experience in AI/ML, data services, a marketplace with reusable inventory and resale economics, services, or manufacturing.
  • Familiarity with ARR-style metrics and acceptance-based revenue recognition.
  • Experience preparing board or investor materials, including fundraise data rooms.
  • Use of AI tools and light scripting such as Python to automate recurring analysis.
  • Experience with business intelligence tools such as Looker or Tableau, or planning tools such as Adaptive or Pigment.
  • Background at a top consulting, banking, or finance-rotation program.

About the Company

Snorkel AI

Builds training data and test environments for AI

Snorkel AI builds training datasets and simulated work environments for AI labs and companies developing models and software agents. Its data products combine expert demonstrations, scoring rules, and quality checks, while runnable environments let agents practice tasks such as coding or using business software. The company pairs domain specialists with its own data development technology to generate examples, evaluate model behavior, and refine weak areas through repeated feedback. Customers buy ready-made datasets or commission tailored data and evaluation work, and enterprises also use its specialized agent solutions. Snorkel AI was founded in 2019 and is headquartered in San Francisco, California.

Company size
201-500
Company stage
Late Stage VC
Total funding
$586.2M
Headquarters
San Francisco, CA
Founded
2019

Recently Posted Jobs

Explore more opportunities at Snorkel AI

See more jobs