Senior Pricing & Monetization Data Scientist

Fivetran•Oakland, CA

1d•Hybrid

About The Position

This role sits at the intersection of economics, analytics, product, and strategy. The Senior Pricing & Monetization Data Scientist combines quantitative analysis, customer research, and commercial thinking to shape how Fivetran prices, packages, and monetizes its products. The position partners across Product, GTM, Finance, Analytics, Sales, Marketing, and Legal to develop and deliver pricing initiatives that improve ARR growth, customer adoption, and value realization.

Requirements

5–8 years designing or operating SaaS or sophisticated B2C pricing models.
Advanced degree (PhD/MSc) in Economics, Statistics, Operations Research, Applied Math, or a similar field.
Fluency in SQL and Python for large-scale data analysis.
Hands-on experience with conjoint, MaxDiff, Gabor-Granger, or Van Westendorp surveys and causal experiment design.
Strong attention to detail and data analysis skills, including interpreting results and recommending actions.
A proven record of turning complex models and analyses into recommendations and shipping changes that moved ARR, gross margin, or NRR.
Collaborative approach with Product, Analytics, Finance, Sales, and Legal, with the ability to work from whiteboard through contract terms.
Strong communication and presentation skills, with the ability to influence at the executive level.

Nice To Haves

Experience with usage-based or behavioral pricing.
Proficiency with BI tools such as Looker or Tableau.
Experience with dbt.

Responsibilities

Analyze product usage, deal, financial, and billing data to model pricing, packaging, and monetization scenarios.
Design frameworks to assess willingness to pay, customer value, and price realization across customer segments and product lines.
Research pricing strategies, packaging models, and monetization approaches across comparable and adjacent markets.
Lead pricing and packaging strategy for new product launches, partnering with Product, GTM, and Finance to define commercial models.
Build value-based pricing and econometric models to quantify elasticity, customer ROI, and lifetime value.
Design and execute pricing experiments.
Synthesize quantitative analysis, customer research, and competitive intelligence into executive recommendations that influence pricing strategy.
Conduct customer and prospect research to understand purchasing behavior, value perception, and pricing friction.
Partner with Product, Analytics, Finance, Sales, Marketing, and Legal to deliver end-to-end pricing initiatives.
Define KPIs and dashboards to measure pricing performance and identify optimization opportunities.
Continuously evolve pricing and packaging strategy to improve ARR growth, customer adoption, and value realization.