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 🧩 

Wallapop generates billions of data points daily. With a mature data infrastructure already in place, our Data Science and Machine Learning area is gaining significant momentum. As we scale, we face the exciting challenge of taking our ML Platform to the next level to support complex solutions in Personalization, Search, Trust & Safety, and Logistics. As a Senior ML Engineer, you will lead the evolution of our ML Platform and MLOps practice. You will partner with Data Scientists, Data Engineers, and DevOps to shape a vision that balances innovation with reliability, ensuring our models scale efficiently to serve millions of users.

What You Will Do 👇

• Iterate and maintain Wallapop’s ML Platform, identifying opportunities to improve speed, reliability, and maintainability. You will define the long-term vision and roadmap for MLOps.
• Work hand-in-hand with Data Scientists to support their efforts, ensuring they have the tooling to develop, deploy, and monitor scalable models efficiently.
• Define and promote engineering best practices (coding standards, testing, CI/CD) within the ML domain.
• Partner with Data Engineering and DevOps to align ML development with company-wide infrastructure and data governance standards.
• Investigate and integrate new frameworks and tools (e.g., for LLMs or real-time inference) to keep our stack modern and effective.

What We’re Looking For 🔎

• Proven experience building and owning production-ready ML platforms and pipelines. You understand the full lifecycle from experimentation to monitoring.
• Deep understanding of AWS components (SageMaker, Lambda, S3) and container orchestration with Kubernetes.
• Strong software engineering background with proficiency in Python, Git, and CI/CD workflows. You write robust, testable code.
• Experience with real-time ML architectures, leveraging tools like Kafka for low-latency ingestion and inference.
• Hands-on experience with vector databases or semantic search infrastructure (e.g., OpenSearch, Vertex AI), including indexing and retrieval tuning.
• Familiarity with the broader ML toolkit, such as orchestration/tracking tools (Flyte, MLFlow, Feast) and standard libraries (Pandas, Scikit-learn, TensorFlow/PyTorch).
• Professional proficiency in English, with the ability to explain complex technical concepts to diverse stakeholders.

What Would Be A Plus 🚀

• Hands-on experience working with LLMs, RAG architectures, and libraries like LangChain or LlamaIndex.
• Familiarity with Big Data technologies like Spark or Beam.
• Experience with Data Engineering tools such as Airflow, dbt, or Datahub.
• Experience with other cloud platforms like GCP or Azure in addition to AWS.

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.

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 plan for free shipping, bumps & home-pick-up on our services
• 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.
• Technical Task - you will be assigned a challenge to assess the technical skills required for the role.
• Expertise Interview - run by the core team, focusing on the hard skills and the ability to deliver in a given context. This usually takes 60-90 minutes.
• Stakeholder Interview - run by the hiring team and relevant stakeholders, focus on the ability to collaborate & deliver in a cross-functional set-up. This usually takes 60 minutes.
• Culture-Add 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.

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 🔍

• Experience working with Search, recommendations & Ranking models in production environments

• 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).

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.

We are now expanding our data capabilities and seeking an experienced Head / Director of Data Science to lead and scale our Data Science UA team function in Barcelona.

This role is ideal for a leader with a strong technical background, excellent people-management skills, and the ability to turn data into actionable, high-impact product and business outcomes.

Role Overview:

The Head / Director of Data Science will be responsible for building and growing our Data Science organization, driving advanced analytics and ML initiatives, and ensuring our products and business units are empowered by high-quality insights and predictive capabilities.

You will work closely with Product, Engineering, Revenue, and Leadership teams to translate business needs into DS/ML solutions, strengthen our data infrastructure, and support decision-making across the ecosystem.

This is a strategic and hands-on leadership role with significant influence on product evolution, optimization algorithms, and operational excellence.

Key Responsibilities:

Leadership & Strategy

• Lead and scale the Data Science function across the organization.
• Translate business and product goals into clear DS/ML initiatives and execution plans.
• Build and promote a strong data-driven culture across all teams.
• Applied Data Science & ML.
• Oversee development, deployment, and monitoring of ML models across Appodeal’s product and monetization ecosystem.
• Guide experimentation, modeling, uplift measurement, and algorithmic optimization.
• Ensure model quality, reliability, fairness, and performance at scale.
• Collaboration & Stakeholder Management.
• Partner with Product and Engineering teams to integrate Data Science into product roadmaps.
• Work with business units to identify opportunities, define DS/ML requirements, and deliver impactful insights.
• Communicate DS outcomes, metrics, and recommendations to leadership.

Team Leadership

• Lead, mentor, and develop a multidisciplinary team of Data Scientists, Analysts, and ML/AI specialists.
• Foster knowledge sharing, best practices, experimentation, and continuous improvement.
• Drive hiring, talent development, and team structure optimization.

Data Infrastructure & Governance

• Collaborate with Data Engineering and MLOps teams to ensure robust pipelines, feature stores, and model deployment workflows.
• Improve data quality, observability, and governance standards.

Qualifications:

Education

Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Math, or a related field (PhD is a plus).

Experience

• 5+ years of experience in Data Science, Machine Learning, or Applied Analytics.
• 3+ years in a DS leadership role (Lead DS, Head of DS, Director of DS, or similar).
• Demonstrated experience building and leading Data Science teams.
• Proven track record of delivering DS/ML solutions with real business impact.

Technical Skills

• Strong understanding of ML algorithms, experimentation, predictive modeling, and statistical analysis.
• Hands-on experience with Python, ML frameworks (TensorFlow, PyTorch, Scikit-learn), and analytics tooling.
• Solid understanding of data pipelines, big data technologies, and collaboration with Data Engineering teams.
• Experience with AdTech, attribution, auction mechanics, or optimization algorithms is a strong plus.

Leadership & Soft Skills

• Excellent stakeholder management and communication skills.
• Ability to translate technical concepts into business language.
• Strong decision-making and prioritization abilities.
• Passion for mentoring, coaching, and building high-performing teams.

What We Offer:

• Opportunity to build and lead the Data Science function of a global product company.
• Direct influence on product roadmap and business outcomes.
• Collaborative and international team environment.
• Competitive compensation package and growth opportunities.
• A chance to shape the future of mobile app monetization.