Staff Data Scientist

Wallapop

Wallapop is a Barcelona based scale-up driven by the purpose to empower people to embrace a more conscious and human way of consumption. We believe in a world where collaborative economy is mainstream. This is what drives us💫. Wallapop operates in Spain, Italy and Portugal, offering a catalogue of several hundreds of millions of products and services. Powered by technical innovation and continuous improvement, we bring together the scale & trust of classifieds with the marketplace’s convenience & reach. Our mission is to enable a connected trade ecosystem, making 2nd-hand the norm through smart use of technology.   The Challenge 🧩 We are seeking an experienced Experimentation lead who will own the evolution of Wallapop's experimentation practice. This person will define the company's experimentation standards, improve statistical rigor, increase the speed and quality of product decisions, and help Product teams adopt a culture of evidence-based decision making. You will partner closely with Product, Engineering, Data Science, Analytics, and Executive leadership to ensure experiments are designed, executed, analyzed, and interpreted consistently across the organization. You will be both a hands-on expert and an internal consultant, helping teams answer critical questions about marketplace growth, personalization, search, discovery, trust & safety, monetization, and seller experiences.   What You Will Do👇 * Experimentation Strategy: Define Wallapop's experimentation vision and roadmap, establish company-wide standards, create frameworks for experiment prioritization, and develop guardrail metrics and governance. * Statistical Excellence: Own methodology across the company and introduce advanced techniques (CUPED, sequential testing, network effect measurement, marketplace methods, quasi-experimental designs, and incrementality measurement) to reduce decision latency. * Product Partnership & Enablement: Act as a strategic advisor and coach to Data Analysts, Data Scientists, and PMs on hypothesis development, experiment design, and success metrics to raise overall experimentation maturity. * Education: Build Wallapop's experimentation curriculum, deliver training programs for PMs, Designers, Engineers, and Analysts, and establish playbooks and office hours. * Platform & Tooling: Partner with Data Engineering and Analytics Engineering to improve infrastructure, evolve Amplitude Experiment data practices, and define quality standards for exposure logging. * Marketplace Optimization: Design experimentation approaches for search ranking, recommendations, personalization, marketplace liquidity, supply-demand dynamics, seller growth, trust & safety, and ads monetization. What We’re Looking For 🔍 * Technical Expertise: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). * Tooling & Code: Strong SQL proficiency along with experience using Python or R.  * Product Partnership: Proven ability to partner directly with Product organizations and influence senior stakeholders using strong business judgment. * Leadership: Demonstrated success building experimentation cultures, experience coaching PMs and analysts, and excellent communication skills. What Would Be A Plus 🚀  * Experience in Amplitude  * Experience working in marketplaces, e-commerce, consumer internet, or two-sided platforms. * Experience with recommendation systems or search systems.   Do note that all our jobs are 📍 Barcelona based. We follow a hybrid model where flexibility rules. We commit to a minimum of 6 days per month in the office. Each team self-organizes to decide on cadence and in-person/remote rituals. Wallapop is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees as we want Wallapop to be a place for everyone. We sponsor visa processes for international candidates when applicable and provide legal & admin support along the process combined with a competitive relocation package. Additionally to the opportunity to contribute to an agile product set up and work together towards achieving our meaningful mission, we offer the following 🍭 Perks & Benefits: * Generous individual learning budget of 2K per year * Free office meals, lunch selection from different providers * Group and individual English, Catalan & Spanish lessons as part of our working day * Private Health Insurance with Alan * Flexible working hours + intensive Fridays * Flexible remuneration to deduct from gross salary (kindergarten/food/transport check) * Gym & Wellness plan, including physiotherapist in the office * Generous referral Program & Charity Donation * Bonus for weddings & newborns * Wallapop Renta (Tax income support) * Monthly product advantages (Wallapop Club) * Work anniversary Gifts and Birthday Surprises * Contribution towards your WIFI in your monthly payroll * One-off payment based on compensation package to go towards setting up your home office * Relocation package (monetary support and legal advice) and visa sponsorship, if applicable * 26 holidays per year * TOP hardware of your choice (latest Apple or Windows)   What does the hiring process for this position look like? 👀 **Please, note that all interviews take place remotely over hangouts.** Intro Call - run by talent acquisition, focus on providing more information about the role and the company as well as going over your experience, motivation, and expectations. This usually takes 45-60 minutes. Task - you will be assigned a task to submit within 5 up to 7 days where you will be able to showcase your expertise and technical skills required for the role. Expertise Interview - run by the hiring team, focus on the required core skills and the ability to deliver in a given context. This usually takes 60-90 minutes. Stakeholder Interview - run by relevant stakeholders reflecting the reality of the context of the role, focus on the ability to collaborate & deliver in a cross-functional set-up. This usually takes 60 minutes. Culture Interview - run by culture interviewers, focus on adherence to Wallapop's purpose and business proposition. This usually takes 60 minutes.  Offer - should you be the right candidate, your offer will be discussed over a call with talent acquisition and will then be confirmed in writing.

Veepee

Pioneer of online flash sales since 2001 and key player in European e-commerce, Veepee collaborates with over 7,000 brands to offer highly discounted products available for a limited time. Operating across various sectors, including fashion, home, wine, travel or beauty... Veepee achieved a turnover of 3.3 billion euros incl. VAT in 2024 and employs 5,000 staff members across 10 countries. As a data scientist at Veepee, you will join our Data Science Team of 20 people, fully cloud-native and distributed between Paris, Barcelona and Brussels. Your main mission will be to build, deploy and maintain state-of-the-art machine learning algorithms. A key focus of this role is the improvement of our price recommendation algorithm — a strategic initiative to optimize margin per visitor. You will also contribute to other core topics such as demand forecasting, product recommendation, genAI pipelines, image recognition…

Veepee

Pioneer of online flash sales since 2001 and key player in European e-commerce, Veepee collaborates with over 7,000 brands to offer highly discounted products available for a limited time. Operating across various sectors, including fashion, home, wine, travel or beauty... Veepee achieved a turnover of 3.3 billion euros incl. VAT in 2024 and employs 5,000 staff members across 10 countries. 📄 JOB DESCRIPTION   As a Data Scientist, you’ll join our Data Science team, distributed across Paris, Lyon, Barcelona, and Brussels. The team focuses on implementing, maintaining, and continuously improving our recommender systems. Today, we deliver personalized sales recommendations to millions of users in real time—and we’re now scaling to include hundreds of thousands of products. You will design and experiment with algorithms that power personalized recommendations across millions of users. Y ou’ll work with large-scale behavioral and product data to build models that increase engagement and conversion, collaborating closely with ML and Data Engineers to move your ideas to production.