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# Senior Data Scientist (H/F)

- **Company:** Umatr
- **Location:** Vitoria-Gasteiz, Spain
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Business Analytics Applications, Big Data, Continuous Integration, Database Queries, Monitoring of Systems, Python (Programming Language), Machine Learning, Power BI, Tensorflow, Tableau (Software), Cloud Platform System, Pytorch, Data Analytics, Machine Learning Operations, Streamlit Framework, Docker
- **Published:** September 9, 2026
- **Apply:** https://www.buscojobs.com.es/senior-data-scientist-h-f-en-vitoria-ID-370189794

## About the Role

They're looking for a Senior Data Scientist to work at the intersection of financial-product research, AI and decision intelligence.
You'll tackle ambiguous commercial problems across credit, lending and investment, turning complex financial data into models, insights and practical AI-powered solutions.
You'll work closely with investment, credit, treasury, Data Science and Engineering teams, helping identify where data and AI can create meaningful commercial advantage.
Research new financial domains, products and commercial problems to understand where data and AI can create value Identify, assess and structure relevant financial and alternative data sources Develop models and analytical approaches across areas such as credit scoring, risk assessment, cash-flow forecasting and portfolio analysis Translate complex quantitative analysis into clear recommendations, summaries and decision-support tools 6+ years of experience in Data Science, Quantitative Modelling or AI/ML ~ Strong foundations in machine learning, statistics and data science ~ Advanced Python and strong SQL skills ~ Experience taking an ambiguous business problem and independently turning it into a data-driven solution or working prototype ~ Strong understanding of how to assess data quality, identify useful signals and validate model outputs ~ Familiarity with MLOps, MLflow or model monitoring Experience creating simple dashboards or user-facing analytical tools using Streamlit,
Tableau or Power BI Exposure to PyTorch or TensorFlow Experience with financial data platforms, alternative data or large-scale datasets Familiarity with cloud environments, APIs, Docker or CI/CD

## Description

We're working with a fast-growing financial technology company based in Abu Dhabi, UAE using AI and decision science to transform how businesses access and deploy growth capital.They're looking for a Senior Data Scientist to work at the intersection of financial-product research, AI and decision intelligence.You'll tackle ambiguous commercial problems across credit, lending and investment, turning complex financial data into models, insights and practical AI-powered solutions.You'll work closely with investment, credit, treasury, Data Science and Engineering teams, helping identify where data and AI can create meaningful commercial advantage.Research new financial domains, products and commercial problems to understand where data and AI can create value Identify, assess and structure relevant financial and alternative data sources Develop models and analytical approaches across areas such as credit scoring, risk assessment, cash-flow forecasting and portfolio analysis Translate complex quantitative analysis into clear recommendations, summaries and decision-support tools 6+ years of experience in Data Science, Quantitative Modelling or AI/ML ~ Strong foundations in machine learning, statistics and data science ~ Advanced Python and strong SQL skills ~ Experience taking an ambiguous business problem and independently turning it into a data-driven solution or working prototype ~ Strong understanding of how to assess data quality, identify useful signals and validate model outputs ~ Familiarity with MLOps, MLflow or model monitoring Experience creating simple dashboards or user-facing analytical tools using Streamlit, Tableau or Power BI Exposure to PyTorch or TensorFlow Experience with financial data platforms, alternative data or large-scale datasets Familiarity with cloud environments, APIs, Docker or CI/CD


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