Data Scientist -Search

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 🧩

Our platform generates vast amounts of data. With a mature infrastructure already in place and a growing team, the opportunities to make a tangible impact are endless. As a Data Scientist, you will improve marketplace dynamics by working on end-to-end ML solutions—from data gathering and prototyping to deployment and iteration.

As a Data Scientist in the Wallapop you will be working on the Data Science and Machine Learning initiatives aimed at improving the whole marketplace dynamics. This will include topics such as improving models that power users' main interaction point:  Search.  You will also look into various models that will help users discover new items through ranked Recommendations, Similar Items, and more.

You will work closely with other Data Scientists, Product Managers, Engineers, UX Researchers, and Analysts to understand the product requirements and explore possible data and ML solutions. You will own the whole product lifecycle, from gathering the data needed to prototyping, building, evaluating, and iterating end-to-end solutions, all within Wallapop’s Data and ML Platforms.

Additionally, you will have the opportunity to work on internal research projects, exploring new technologies and building PoCs that could ultimately become data products or insights, and be valuable for Wallapop.

What You Will Do👇

• Collect, clean, and analyze large datasets from diverse sources, including user behavior, transactions, and market trends.
• Develop and implement machine learning models to solve business problems, such as personalized recommendations and search.
• Work with multidisciplinary Product teams to identify opportunities and gather requirements (both in terms of product and tech).
• Own initiatives from start to deployment:  ideation, data processing (ETL), modeling, testing, deployment, monitoring and iteration (w/ help from Engineering partners)
• Proactively suggest, research and prototype new ideas for data and ML solutions.
• Communicate complex data insights to both technical and non-technical audiences, including stakeholders involved in marketplace operations.

What We’re Looking For 🔍

• Problem-Solving Core: A degree in a quantitative field (Engineering, Math, Stats, Physics) or equivalent practical experience in data science.

• Software Mindset: Proficiency in Python and the ability to write clean, maintainable code for ML applications.

• Production Experience: A proven track record of building and deploying data products that solve business challenges in a production environment.

• Data Fluency: Advanced SQL skills and experience handling large datasets (knowledge of libraries like Pandas or Scikit-learn is highly valued).

• Growth Orientation: A desire to learn new technologies and an ability to adapt your technical approach to the problem at hand.

• Algorithmic Foundation: Solid understanding of Machine Learning fundamentals, specifically as they apply to personalization or recommender systems (e.g., collaborative filtering, content-based filtering, or deep learning for embeddings).
• Experience working with Search, recommendations & Ranking models in production environments

What Would Be A Plus 🚀

• Experience working within an eCommerce or Marketplace platform, or in a product-tech company.
• Experience working within the Logistics, Trust & Safety or Customer Service domains.
• Experience working within the AWS cloud (Redshift, S3, Lambda), and with cloud MLaaS solutions such as Amazon SageMaker (preferably), but also Google Vertex AI, Microsoft Azure ML, and other MLOps tools (MLFlow, Flyte, Feast, Kubeflow, etc).

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.