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# Data Scientist

- **Company:** Jobgether
- **Location:** Spain (Remote available)
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Big Data, Data Infrastructure, Data Visualization, Fraud Prevention and Detection, Python (Programming Language), Machine Learning, Tableau (Software), Performance Monitor
- **Published:** August 12, 2026
- **Apply:** https://es.trabajo.org/oferta-4021-c6687168b91061952fef8c5471090b08

## About the Role

into impactful analytical solutions. - Support the development of innovative risk mitigation strategies while balancing security, efficiency, and user experience. Requirements: - 7+ years of experience in data science, quantitative modeling, analytics, or related data-focused roles, ideally within fraud prevention, financial risk, or fintech environments. - Strong hands-on expertise in Python and/or R, along with advanced SQL skills for large-scale data analysis. - Experience with machine learning model development, deployment, and performance monitoring in production environments. - Proficiency with BI and visualization tools such as Tableau, Sigma, Metabase, or similar platforms. - Strong analytical skills, including experience with exploratory data analysis, cohort analysis, and extracting insights from complex datasets. - Ability to communicate technical findings effectively to both technical and non-technical audiences, including external stakeholders and clients. - Excellent

## Description

build, and deploy machine learning models to identify and prevent fraud across a variety of fintech and risk-related use cases. - Drive a data-first culture by promoting analytical thinking and data-driven decision-making across internal teams and client engagements. - Develop, monitor, and optimize performance metrics to measure the effectiveness of risk strategies and product outcomes. - Conduct advanced analyses to uncover insights that improve fraud prevention, approval rates, and overall customer experience. - Partner directly with clients to understand their fraud challenges and provide clear, actionable recommendations based on data insights. - Build automated dashboards and self-service reporting solutions using business intelligence tools. - Collaborate closely with engineering teams to productionize models, improve scalability, and enhance data infrastructure. - Work cross-functionally with product, business, and engineering stakeholders to translate business requirements


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