Staff Data Scientist, Experimentation

About the role

This position defines and owns Wallapop's experimentation practice, setting the standards and governance that accelerate product decisions across the organization. You will architect the end-to-end experimentation lifecycle, from hypothesis generation and experimental design to analysis, interpretation, and knowledge dissemination. The role requires building robust guardrails and processes that ensure statistical rigor, measurement validity, and reliable inference across the product surface. You will partner directly with Product, Design, and Engineering to embed data-driven thinking into the core of product roadmaps and release criteria. A significant portion of the role focuses on reducing decision latency by creating a structured, scalable experimentation roadmap supported by clear standards. You will own the development of playbooks, training curricula, and office hours to elevate the analytical capability of PMs, designers, and analysts company-wide. Success in this role is measured by the maturity of the experimentation culture, the quality of insights generated, and the tangible business outcomes unlocked through rigorous testing.

Key facts

What you'll do

Product and engineering outcomes accelerate through experimentation roadmaps, standards, and governance that reduce decision latency.

A structured experimentation curriculum delivers training for PMs, Designers, Engineers, and Analysts, supported by playbooks and office hours to build capability.

Requirements

8+ years of total experience in data science, product analytics, or causal inference, including at least 4 years deeply focused on experimentation (experimental design, statistical inference, A/B testing, and variance reduction).

Strong SQL proficiency along with experience using Python or R enables analysis and tooling for experimentation.

Direct partnership with Product organizations and influence over senior stakeholders using strong business judgment drives impact.

Building experimentation cultures, coaching PMs and analysts, and excellent communication skills ensures team maturity.

Nice to have

Experience in Amplitude supports instrumentation and analysis consistency.

Experience working in marketplaces, e-commerce, consumer internet, or two-sided platforms informs domain-specific experimentation.

Experience with recommendation systems or search systems enhances optimization practices.

Practical notes

Typical interview steps

Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model. Some companies give a take-home analysis. Expect questions about past projects and the business impact of your work. Interviewers often evaluate how you communicate uncertainty and business impact, not only the math. Bringing a clean write-up of a past analysis to the interview is well received.

Good to know

Common tools include SQL, Python or R, Amplitude Experiment, and exposure logging frameworks.

The position emphasizes coaching cross-functional teams and building data-driven decision practices.

Work involves designing experiments for core marketplace levers such as search, recommendations, liquidity, trust & safety, and monetization.

The company provides learning budgets, wellness benefits, and flexible working arrangements.

Questions to ask

Useful questions for the interview: what a typical week looks like, how work is assigned, what tools the team uses, and how feedback works. Asking how the role has changed recently and what the team wishes it had known when joining is also reasonable. Questions about the manager's priorities are especially valued.

Career growth

Data careers grow toward senior analyst, staff data scientist, or data engineering lead. Many professionals specialize in machine learning, analytics, or infrastructure. Cross-functional work with product and engineering teams becomes more important at senior levels. The field changes quickly, so continuous learning is part of the job. Professionals who can translate numbers into decisions tend to advance fastest.

About Wallapop

Wallapop is hiring for Staff Data Scientist, Experimentation. The listing location is Barcelona.

This Staff Data Scientist, Experimentation opening is posted for Barcelona.