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Analytics

Predictive Analytics Solution Engineer

New York, USA Full-time Hybrid

Plumb is spend-to-revenue analytics for subscription businesses. We unify ad spend and subscription revenue into one source of truth and reconcile it to a single, trustworthy number: the one a finance team can actually run on. As a Solution Engineer, you’re the person who makes that real for each customer.

About the role

You’ll be the technical and data point of contact for a portfolio of customers, from their first connected source to the moment they trust the numbers on their dashboard. It’s a role for someone who’s equally comfortable in a SQL warehouse and in a room full of growth and finance leaders, translating messy, real-world data into answers people can act on.

What you’ll do

  • Guide customers through onboarding onto Plumb, connecting ad channels and revenue sources, then shaping them into working metrics and reports.
  • Turn ambiguous business questions into concrete analysis, and explain reconciliation, ROI normalization, and cohorts in plain language.
  • Serve as the primary data and technical contact for your accounts, understanding each business deeply enough to anticipate what they need.
  • Diagnose and resolve data and pipeline issues, and know when a one-off fix should become a permanent one.
  • Feed recurring customer needs back to the product team, and collaborate to turn them into product.
  • Help customers reach the point where the hard budget decisions make themselves.

What we’re looking for

  • 2–4 years in a customer-facing analytics, solutions, or data role, ideally in B2B SaaS.
  • Fluent in SQL and comfortable working directly in a data warehouse.
  • A track record of turning open-ended business questions into insight that changed a decision.
  • Excellent communication and interpersonal skills: you can hold the trust of both technical and non-technical stakeholders.
  • Able to run several accounts in parallel and prioritize well.
  • A proactive, adaptable, startup-builder mindset.

Nice to have

  • Experience with subscription or marketing analytics: CAC, LTV, ROAS, retention.
  • Python, and familiarity with BigQuery or AWS.