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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** Preply Inc. - **Location:** Barcelona, Spain - **Contract:** Permanent contract - **Skills:** A/B Testing, Artificial Intelligence, Airflow, Data Analysis, Information Engineering, Extract Transform Load (ETL), Data Systems, E-Business, Python (Programming Language), Machine Learning, SQL Databases, Snowflake, Apache Spark, Data Strategy, Software Coding, Looker Analytics, Data Pipelines, Databricks - **Published:** July 17, 2026 - **Apply:** https://www.jobleads.com/es/job/ecc098ebb47de94c4587d04db2f3810f4 ## About the Role * An AI mindset: you use AI to boost your efficiency, love working agentically, automate processes, and enable your stakeholders with AI; * A pragmatic problem-solver at heart: you dig into complexity to find the simplest, most elegant path through it, guided by curiosity rather than a love of complicated models; * Extensive experience as a Data Scientist working with performance marketing teams in a B2C environment, delivering business insights and building data products; * Knowledge of incrementality and attribution; * Skilled in developing and deploying machine learning models; * Experience with experimentation (design and evaluation of A/B tests); * Experience working in Marketplaces and/or digital business environments, in the context of performance marketing; * Strong coding skills in SQL and Python; * Creative mindset and proactive attitude towards the creation and evaluation of new solutions; * Strong curiosity, problem solving and problem finding skills; * Advanced written and verbal communication skills in English., * Previous experience with causal inference techniques (e.g. geo-lift testing, causal impact, synthetic control, difference in differences, etc.) * Previous experience with Databricks, Snowflake, Looker; * Previous experience with Apache Spark, * Knowledge of data orchestration tools (e.g. dbt and Airflow). ## Description At Preply, we're growing a talented Data Team to empower top-notch decision-making across our organization. Our team collaborates closely with various other chapters - including product, business, and platform - leveraging analysis, experimentation, causal inference, and machine learning. You'll be embedded in cross-functional teams, partnering with our MarTech Product Manager, Marketeers, Tech Leads, and the Data Strategy team. Check out our Tech Radar to see the tools and technologies we love using at Preply! What you'll be doing * Collaborate with performance marketing teams in coming up with data solutions to support the optimization of marketing campaigns, budgets and results; * Roll out Marketing Mix Modeling (MMM) to more countries and help build an automated MMM budget platform using advanced Bayesian statistics; * Design and analyze incrementality tests to measure marketing effectiveness, applying advanced methods like causal inference to quantify incremental ROI; * Design a unified system that connects the dots between MMM and incrementality results; * Shape the testing roadmap; * Design our Creative Analytics framework, developing new metrics such as creative fatigue to help scale new channels; * Improve targeting and bidding strategies by using regression models to assign predictive weights to funnel events; * Act as a sparring partner to our Applied AI team: support the roll-out of models, analyze their impact, understand feature importance, and bring both business and data science knowledge to guide these projects; * Work closely with the Data Engineering team in the creation of scalable data pipelines while guaranteeing an optimal evolution of our ETL processes, as well as the adoption of new tools and frameworks; * Contribute to cross-company initiatives in alignment with our data organization's vision; * Support proactively the application of predictive models in performance marketing channels. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)