Senior Data Scientist

Shalion is a data and insights-driven company that serves world-class manufacturers and brands globally. Through our Digital Shelf Optimization, Retail Media, and Food Service Aggregators solutions, we provide innovative tools for e-commerce monitoring.
At Shalion, we empower brands to make smarter business decisions in eCommerce by delivering actionable data and insights on online product prices, availability, share of search, and more. We operate across 1000+ e-retailers in 60+ countries, serving industry giants such as Heineken, Lego, Danone, Nestlé, Diageo, and JDE.
As a leader in data intelligence, we specialize in gathering, analyzing, and applying proprietary artificial intelligence to deliver relevant data and monitoring tools, helping our clients maximize their e-commerce performance.
The role
As a Senior Data Scientist, you will join our Data Science team and work on advanced analytics problems at the core of our product, such as measuring the real impact of brands’ actions (retail media campaigns, promotions, pricing or availability changes) on their sales. You will work with very large datasets collected daily across 1000+ e-retailers in 60+ countries.
We are looking for someone with strong analytical judgement and a good understanding of causal methods, who cares about getting a reliable answer into the product more than about the most sophisticated model. You will work close to the business and product teams, so explaining results clearly matters as much as producing them.
Your Responsibilities
Design and develop impact measurement solutions for our clients, from the analytical approach to a solution that can run at scale.
Explore and analyze large-scale e-commerce data (prices, availability, search, retail media and sales) efficiently, to understand what drives sales, and validate that results make business sense.
Choose the right level of complexity for each problem: start simple, iterate, and add sophistication only when it brings real value.
Work with Product, Data Engineers and ML Engineers to turn analyses and models into features of our platform.
Communicate findings and limitations clearly to non-technical colleagues and, when needed, to clients.
Share knowledge within the team and support less experienced data scientists.
Your profile:
4+ years of experience as a Data Scientist or in an advanced analytics role, with solutions used in a real business context.
Strong analytical background: statistics, experimentation (A/B testing) and working with messy, real-world data.
Knowledge of causal inference methods (e.g. difference-in-differences, synthetic control, matching, uplift models) and when each one makes sense.
Strong Python and SQL skills, with hands-on experience working efficiently with large datasets.
Ability to explain technical results in a simple way.
Fluent English & Spanish.
(Bonus) Experience in e-commerce, retail media, marketing measurement or CPG.
(Bonus) Experience with cloud environments (AWS preferred) and data platforms such as Snowflake.
Soft Skills
You value scientific rigor just as much as simplicity.
You want to understand the client's problem, not only the data.
You question results and are honest about what the data can and cannot tell.
You are a team player, comfortable working with people from different backgrounds and roles.
What We Offer
🌍 An international team – Work with colleagues from 10+ nationalities.
🚀 A dynamic and innovative environment – Be part of a high-performing team
🏢 Hybrid work model – 3 days in-office, 2 days remote.
💡 Impactful work – Contribute to a challenging and innovative project.
🎟 Flexible benefits – allocate part of your gross salary (pre-tax) to meal vouchers, transport allowance, and private healthcare at a preferential rate.
🍏 Office perks – Fresh fruit and specialty coffee daily.
📄 Contract – Permanent
📍 Great location – Office in Barcelona’s Sarrià-Sant Gervasi district.
Shalion Data Services Limited is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Work arrangement
No