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# Data Scientist

- **Company:** Solicitante De Empleo
- **Location:** Spain (Remote available)
- **Contract:** Temporary to permanent
- **Skills:** Amazon Web Services, Data Analysis, Microsoft Azure, Cloud Computing, Python (Programming Language), Machine Learning, Standard Sql, SQL Databases, Model Validation, Git, Information Technology
- **Published:** September 25, 2026
- **Apply:** https://www.recruit.net/job/data-scientist-jobs/431350A8E6CE2F8D

## About the Role

* 1-2 years in an Analytics or Data Science team
 * Degree in Computer Science, Data Science, Statistics, Mathematics, Economics, or a related quantitative field
 * Strong coding in Python or R (both is a plus)
 * SQL
 * Solid statistics: regression, machine learning fundamentals, and model validation
 * Working understanding of Bayesian methodologies
 * Comfortable with Git
 * Fluent English, written and spoken
 * Intellectually curious, organised, and able to work independently on well-scoped problems

Nice to have

 * Hands-on Bayesian tooling (Stan, PyMC, brms, or similar)
 * Cloud familiarity (AWS, Azure, or GCP)
 * Experience in media, marketing, or marketing-effectiveness work
 * Time series, causal inference, or test design

## Description

Gain full access to exclusive job listings from leading companies worldwide.

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Receive expert feedback with personalized suggestions to enhance your resume., You will join our Data Science team and help turn client data into reliable models and reusable analytics tooling. This is a hands-on modelling and engineering role: you will spend your time on data, code, and statistical methods., * Prepare, clean, and quality-check datasets using SQL and Python or R

 * Build and validate statistical models, including regression, machine learning, and forecasting
 * Apply sound statistical thinking, including a working understanding of Bayesian ideas (priors, uncertainty, posterior interpretation)
 * Automate recurring analysis so the team can reuse pipelines, functions, and tools
 * Use Git to work with the team's codebase
 * Document methods and results clearly so others can review, rerun, and present the work


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