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Senior data scientist, hibrido

Madrid
Indefinido
Jordan Martorell
Publicada el 26 enero
Descripción

Senior Data Scientist
Overview
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 marketplaces convenience reach. Our mission is to enable a connected trade ecosystem, making 2nd‐hand the norm through smart use of technology. Backed by top investors such as Accel, Insight Partners and Naver Corp we bring our total valuation to 806 million EUR and are embarking on our international journey with the aim to become the world's best unique goods trading platform.

The Challenge
The Wallapop platform generates tons of data and, with a mature data infrastructure already in place, the team is experiencing significant growth and, with many initiatives down the road, the opportunities are endless. As a Data Scientist you will be working on the Data Science initiatives aimed at improving the whole marketplace dynamics. 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 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 behaviour, transactions, and market trends.

Develop and implement machine learning models to solve business problems, such as personalised recommendations, fraud detection, and pricing optimisation.

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), modelling, testing, deployment, monitoring and iteration (with 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

Bachelor or MSc degree in engineering, mathematics, statistics, physics, or another quantitative field.

Strong coding skills (Python is a must, but other languages are also valued), capable of building robust data and ML software.

Experience building complex data products and ML solutions to real‐life problems in a production‐oriented environment, identifying the right techniques to solve the problem at hand.

Experience with common libraries and frameworks such as Pandas, Numpy, Scikit‐learn, TensorFlow, Keras, PyTorch.

Advanced in SQL, capable of getting the data required from the appropriate sources, and building and maintaining data pipelines if needed (experience in tools such as Airflow or DBT would be a plus).

Excellent communication and presentation skills, with the ability to explain data insights to business stakeholders in the context of marketplace dynamics.

What Would Be A Plus

Experience working with Search Ranking models in production environments.

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).

Location, Model & Perks
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‐organises to decide on cadence and in‐person / remote rituals.

Equity, Inclusion & Benefits
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.

Competitive phantom shares package for all employees

Generous individual learning budget of 2k per year

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‐pickup 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

Additional Details

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)

ETL, Python, SQL, Pandas, Numpy, Scikit

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