Senior Data Scientist | Relocation To Uae

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 aSenior Data Scientistto 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 DoResearch new financial domains, products and commercial problems to understand where data and AI can create valueIdentify, assess and structure relevantfinancial and alternative data sourcesDevelop models and analytical approaches across areas such ascredit scoring, risk assessment, cash-flow forecasting and portfolio analysisTake ambiguous problems from initial hypothesis through toMVP, validation and iterationExplore opportunities to automate financial and investment workflows using AIBuild practical AI solutions, includingLLM, RAG and agent-based workflows, where they add genuine valueTranslate complex quantitative analysis into clear recommendations, summaries and decision-support toolsPresent findings and recommendations toinvestment, credit and business stakeholdersWhat We’re Looking For6+ yearsof experience in Data Science, Quantitative Modelling or AI/MLStrong experience in afinancial domain, ideally private credit, lending, underwriting, credit scoring, banking or riskExperience with areas such asdefault modelling, LGD, model validation, credit risk or fixed-income productsis highly valuableStrong foundations inmachine learning, statistics and data scienceAdvancedPythonand strong SQL skillsExperience taking an ambiguous business problem and independently turning it into adata-driven solution or working prototypeStrong understanding of how to assess data quality, identify useful signals and validate model outputsPractical understanding of modern AI approaches such asLLMs, RAG, agents and orchestrationNice to HaveExperience withprivate credit, investment management, lending or financial productsExperience withXGBoost, LightGBM, SHAP or other predictive modelling techniquesExperience building AI-powered internal tools or prototypesFamiliarity withMLOps, MLflow or model monitoringExperience creating simple dashboards or user-facing analytical tools usingStreamlit, Tableau or Power BIExposure toPyTorch or TensorFlowExperience with financial data platforms, alternative data or large-scale datasetsFamiliarity with cloud environments, APIs, Docker or CI/CDExperience withMCP or agent-based systemsInterested?Apply today!

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