Senior Data Scientist | Relocation To Uae

Umatr; Ibiza; Presencial; EUR 103.000 - 155.000; Jornada completa

Descripción de la vacante

Umatr, a fast-growing fintech, seeks 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 collaborate with investment, credit, treasury, Data Science and Engineering teams, helping identify where data and AI can create meaningful commercial advantage.

Formación

• 6+ years in Data Science or AI/ML roles.
• Strong Python and SQL skills.
• Experience turning ambiguous problems into data-driven solutions.
• Financial domain experience is highly valuable.

Responsabilidades

• Research financial domains to identify data value.
• Identify data sources and structure data.
• Develop models for credit scoring, risk and cash-flow forecasting.
• Turn hypotheses into MVPs with validation and iteration.
• Explore automation of financial workflows using AI.
• Build AI solutions (LLM, RAG, orchestration) when valuable.
• Summarize findings for stakeholders.

Conocimientos

Data Science experience

Quantitative modelling

AI/ML

Python

SQL

Problem solving

Herramientas

XGBoost

LightGBM

SHAP

Streamlit

Tableau

Power BI

PyTorch

TensorFlow

Docker

MLflow

MLOps

Descripción del empleo

Descripción del trabajo

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.

What You’ll Do

• 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
• Take ambiguous problems from initial hypothesis through to MVP, validation and iteration
• Explore opportunities to automate financial and investment workflows using AI
• Build practical AI solutions, including LLM, RAG and agent-based workflows, where they add genuine value
• Translate complex quantitative analysis into clear recommendations, summaries and decision-support tools
• Present findings and recommendations to investment, credit and business stakeholders

What We're Looking For

• 6+ years of experience in Data Science, Quantitative Modelling or AI/ML
• Strong experience in a financial domain, ideally private credit, lending, underwriting, credit scoring, banking or risk
• Experience with areas such as default modelling, LGD, model validation, credit risk or fixed-income products is highly valuable
• 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
• Practical understanding of modern AI approaches such as LLMs, RAG, agents and orchestration

Nice to Have

• Experience with private credit, investment management, lending or financial products
• Experience with XGBoost, LightGBM, SHAP or other predictive modelling techniques
• Experience building AI-powered internal tools or prototypes
• 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
• Experience with MCP or agent-based systems