Senior Product Analyst; Pricing

At Too Good To Go, we have an ambitious mission: to inspire and empower everyone to fight food waste together.

More than 1/3 of all food produced in the world is wasted. And that has a huge impact on the health of our planet. 10% of greenhouse gas emissions come from food waste and loss.

Through our marketplace app, we connect businesses that have unsold, surplus food, with consumers who can buy and enjoy it at ⅓ of retail value. We are on a mission to empower everyone to take action against food waste: alongside our marketplace app, we create educational tools, explore new business solutions, and influence legislation to help reduce food waste.

We’re growing fast:
Our community of 120 million registered users and 180,000 active partners across 20 countries, have together already saved over 500 million meals from going to waste.

We are looking for a Senior Product Analyst to join our Product Analytics and Center of Excellence team at Too Good To Go, embedded in our newly formed Pricing team in London
.

Pricing shapes what partners earn, what consumers pay, and how much surplus food gets saved. We are building our first dedicated Pricing team, and you will be its analytical lead, partnering closely with our Senior Product Manager for Pricing from day one.

As a marketplace, our pricing challenges are shaped by supply-demand dynamics, partner economics, and consumer behavior
. Demand is often capped by supply rather than price, so standard pricing playbooks rarely apply as they are. You will work on problems such as dynamic pricing, consumer service fees, partner base price recommendations, and Key Account pricing
, across both the Partner and Consumer sides of our marketplace.

Your goal is to make sure every pricing decision is grounded in rigorous measurement. That means saving as much surplus food as possible and growing value for Too Good To Go, our Partners, and our Consumers, rather than shifting value from one side to another.

• Partner with the Senior Pricing PM to shape the team's roadmap, size opportunities, and define the metrics that connect pricing changes to business outcomes

• Lead discovery and deep dives on pricing problems such as:

  • Evaluating and evolving our dynamic pricing logic, and identifying where it under- or over-discounts

  • Understanding how consumer service fees affect revenue, conversion, retention, and meals saved

  • Developing price recommendations for partners, from onboarding through to Key Account deals

• Design and evaluate pricing experiments, including multi-variant and dose-response tests, with statistically sound setup, power analysis, and clear decision criteria

• Apply quasi-experimental methods (e.g. matched controls, difference-in-differences) where randomization isn't possible, and replace before-after reads with reliable measurement of incremental impact

• Build our understanding of price response in a supply-constrained marketplace, and translate short-term effects into long-term outcomes such as retention, meals saved, and GMV

• Define tracking and instrumentation requirements so that pricing experiments measure what they are intended to measure

• Enable the Pricing team and stakeholders to self-serve pricing performance through clear, accurate dashboards in Amplitude and Looker

• Collaborate closely with Data Scientists in the Center of Excellence on modeling, and with Finance, Commercial, and Key Accounts teams on pricing decisions that reach beyond the product

• Communicate findings and recommendations clearly to senior stakeholders, including the Global Management Team

• Take end-to-end ownership, from problem framing through to experiment readouts and impact evaluation

Our analyses are written in SQL and Python, on data stored in Redshift and modeled with dbt. Amplitude is our source of truth for in-app event data, funnels, and experimentation readouts, and Looker for cross-domain, partner, and financial reporting. We actively use AI tools in our day-to-day analytical work.

• Degree educated within a quantitative field (e.g. Statistics, Economics, Mathematics, Computer Science, or equivalent)

• Solid experience in product analytics, data science, or a similar analytical role, with a track record of influencing product decisions through data

• Proven experience building analytics foundations from scratch, such as metrics frameworks, experimentation practices, and reporting, for a new product area or team

• Strong SQL and Python skills for analysis and statistical work

• Hands-on…