This is an Emiratization position — open exclusively to UAE Nationals. An organisation in Dubai is seeking a highly skilled Manager — Data Science, Finance to lead the execution of financial data science projects — enhancing financial performance and managing risk through advanced analytics and machine learning. This strategic senior role oversees a data science team, implements predictive models including residual value prediction, credit scoring, delinquency prediction, and collections optimisation, develops financial KPI dashboards, and generates actionable financial insights — requiring 5+ years of data science and analytics experience with a strong finance focus and proficiency in Python, ARIMA, LSTM, Databricks, TensorFlow, and PyTorch.
About This Data Science Manager Finance Role — Dubai UAE
Mission: Lead financial data science projects that enhance financial performance and risk management through advanced analytics, machine learning, and predictive modelling
Team Scope: Oversee and develop a team of data scientists — managing delivery, quality, and professional growth across financial analytics projects
Predictive Scope: Residual value prediction, credit scoring, delinquency prediction, and collections optimisation — four high-impact financial ML use cases
Success Measure: Actionable analytics solutions that align with business objectives — 2+ predictive use cases, 3 finance dashboards, 3 monthly financial insights
Why This Data Science Manager Finance Role Stands Out
Emiratization Senior Role: A rare senior data science leadership opportunity specifically created for UAE Nationals — combining financial analytics with machine learning at managerial level
High-Value Financial ML Models: Credit scoring, residual value prediction, delinquency forecasting, and collections optimisation — the most commercially impactful ML use cases in financial services
Full Advanced Analytics Stack: ARIMA, SARIMA, Prophet, LSTM, gradient boosting, ensemble methods, and neural networks — applied to real financial data science challenges
KPI Dashboard Leadership: Create and own three comprehensive finance-related dashboards — giving stakeholders actionable, data-driven insight into financial performance and risk
Position Overview
This Manager — Data Science, Finance in Dubai is responsible for leading the execution of financial data science projects — implementing predictive models including residual value prediction, credit scoring, delinquency prediction, and collections optimisation, creating financial KPI metrics and risk dashboards using statistical techniques and data visualisation libraries, generating financial insights through time series decomposition, anomaly detection, and stress testing, managing and mentoring a team of data scientists, communicating complex analytical findings clearly to non-technical stakeholders, and delivering at least 2 successful predictive model use cases, 3 comprehensive finance-related dashboards, and 3 actionable financial insights per month — all aligned with strategic business objectives.
Why This Role Matters: As Data Science Manager — Finance in Dubai, you build the analytical infrastructure that determines how an organisation understands, forecasts, and manages its financial risk and performance. When your LSTM network correctly predicts residual values at the tail of a financing contract, your credit scoring model accurately identifies customers at risk of default before they delinquent, or your collections optimisation algorithm routes recovery efforts where they will be most effective — real financial losses are prevented, capital is protected, and strategic decisions get made with data confidence. At managerial level, you also build the team capability that sustains this impact long after each individual model is deployed.
What You Will Do
Predictive Modelling — Credit, Residual Value & Delinquency
- Implement residual value prediction models — forecasting the end-of-contract value of financed assets with sufficient accuracy to improve portfolio risk management and provisioning decisions
- Build and maintain credit scoring models — assessing applicant credit risk at the point of origination using gradient boosting, ensemble methods, and logistic regression approaches
- Develop delinquency prediction systems — identifying accounts at elevated risk of payment default before delinquency occurs, enabling proactive intervention by collections and risk teams
- Implement collections optimisation models — improving recovery rates by intelligently routing collections resources to the accounts and approaches most likely to produce successful outcomes
- Deliver at least 2 successfully demonstrated predictive model use cases — from data preparation through model training, validation, deployment, and ongoing monitoring
Financial KPI Dashboards & Data Visualisation
- Create financial KPI metrics and risk dashboards using statistical techniques and Python visualisation libraries — Matplotlib, Seaborn, and Plotly — tailored to each stakeholder audience’s decision-making needs
- Develop and maintain 3 comprehensive finance-related dashboards that provide actionable insights to senior financial and risk stakeholders — covering portfolio performance, credit risk, and operational KPIs
- Maintain dashboard accuracy, timeliness, and relevance — updating models, data pipelines, and visualisations as business requirements and data sources evolve
Financial Insights, Time Series & Anomaly Detection
- Generate financial insights using time series decomposition, anomaly detection algorithms, and stress testing methodologies — translating complex analytical outputs into business-relevant strategic recommendations
- Apply ARIMA, SARIMA, and Prophet for time series forecasting — delivering accurate financial projections for revenue, cash flow, and portfolio performance
- Produce 3 actionable financial insights monthly — directly informing decision-making and strategy formulation for senior finance and risk leadership
- Communicate complex technical findings clearly and persuasively to non-technical stakeholders — making data science outputs genuinely useful for business decisions
Required Qualifications & Skills
Essential Requirements
- UAE National (Emiratization): This position is exclusively available to UAE National candidates as part of the organisation’s Emiratization programme
- Bachelor’s or MSc in Financial Analytics, Computer Science, Data Science, or a closely related quantitative field
- 5+ years of experience in data science and analytics — with a strong, demonstrated focus on financial applications including credit risk, forecasting, or portfolio analytics
- Proficiency in Python, SQL, and Databricks — with production-grade data science code quality and workflow management
- Experience with machine learning libraries — Scikit-Learn, TensorFlow, and PyTorch
- Proficiency in time series modelling — ARIMA, SARIMA, and Prophet for financial forecasting
- Experience with LSTM networks for sequence prediction in financial data contexts
- Hands-on MLOps experience and Git version control proficiency
- Strong data visualisation skills — Matplotlib, Seaborn, and Plotly
- Ability to communicate complex technical concepts clearly to non-technical financial and business stakeholders
Key Technical Competencies
- Proficiency in predictive modelling — ARIMA, LSTM, gradient boosting, ensemble methods, and neural networks
- Expertise in machine learning methods applicable to financial risk — credit scoring, delinquency prediction, residual value, and collections
- Strong statistical technique and financial data visualisation skills for dashboard development
- Team leadership and mentoring capability — developing junior data scientists toward independent analytical delivery
About Emiratization — Building UAE National Financial Data Science Leadership
The UAE’s Emiratization programme is actively creating senior career pathways for UAE Nationals in the most strategically important and technically demanding roles in the country’s growing financial services and technology sectors. This Manager — Data Science, Finance position in Dubai represents exactly the kind of high-impact, senior Emiratization opportunity that combines advanced machine learning and financial analytics expertise with team leadership and stakeholder management responsibility — contributing to the UAE’s ambition to develop world-class national talent in data science, artificial intelligence, and quantitative finance. UAE Nationals with the right technical background and a passion for applying data science to real financial challenges are strongly encouraged to apply.
Career Excellence: Lead financial data science at senior managerial level in Dubai — credit scoring, residual value prediction, LSTM, Databricks, and KPI dashboards — exclusively for UAE Nationals.
Who Should Apply?
- UAE National Data Science Managers: With 5+ years of financial data science experience — credit risk, portfolio analytics, financial forecasting — and team leadership responsibility
- Emiratization Financial Analytics Leaders: UAE Nationals with advanced Python, ARIMA, LSTM, and Databricks proficiency — seeking a senior managerial data science opportunity in Dubai’s financial sector
- Credit Risk & Financial ML Engineers: UAE Nationals with production experience building credit scoring, delinquency prediction, and collections optimisation models using gradient boosting and neural network approaches
- Financial Dashboard & KPI Developers: UAE Nationals with Plotly, Matplotlib, and Seaborn visualisation expertise — creating meaningful, decision-supporting financial dashboards for senior stakeholders
- UAE National Financial Data Scientists — Senior Level: BSc or MSc qualified, 5+ years in finance-focused data science, ready to step into a managerial role that combines team leadership, advanced analytics, and strategic financial insight delivery
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