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# Data Scientist

- **Company:** Tipo De
- **Location:** Madrid, Spain (Remote available)
- **Salary:** €48,000.0 - €53,000.0
- **Contract:** Permanent contract
- **Skills:** Data Mining, Data Visualization, Database Queries, Python (Programming Language), Machine Learning, NumPy, Tableau (Software), Data Processing, Pandas, Plotly
- **Published:** August 13, 2026
- **Apply:** https://www.adzuna.es/contact-us.html

## About the Role

+ Previous experience in a Data Science role where you have gained a solid grounding in statistics, probability and core Machine Learning algorithms
 + Proficiency in Python including data manipulation libraries such as pandas or NumPy
 + Strong SQL skills for data extraction and manipulation
 + Experience with data visualisation libraries (malplotlib, seaborn, plotly) and creating reports in tools like Tableau
 + Strong teamworking skills but also the ability to work independently
 + Previous experience processing and exploring data in the iGaming sector would be an advantage but generally an industry involving predicting human behaviour in purchasing such as retail or banking could be suitable

## Description

Our client is an IT consultancy operating on a global scale who are looking to hire a Data Scientist to join their Core Modelling team. Their clients operate in industries where they succeed based on the quality of predictions their operating models are based on. They are looking to recruit a Data Scientist who can get properly stuck into the core modelling work.
You'll be working as part of a small team to build, train and evaluate machine learning models alongside senior team members who'll guide you through the trickier problems. You will own your own workload and be trusted to manage your day-to-day but will have additional support should it be needed.
What You'll actually be doing:

 + Cleaning, processing and exploring client data to find the patterns that matter
 + Building and evaluating Machine Learning models for prediction and classification tasks
 + Update and restrain existing foundation models as new data comes in
 + Working on the pipelines that get models from notebook to production
 + Presenting results clearly and for technical and non-technical stakeholders
 + Turn analysis into reports and visualisations using Tableau and Python


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