Data Science & Risk Analyst

Strategy & Forecasting

• Support execution of the RV methodology and governance framework across all business units.
• Prepare RV assumptions and depreciation curves for leasing, subscription, buy-back agreements, manufacturer programs and fleet operations.
• Forecast used vehicle price index & depreciation using internal and external data sources, AI-driven models and UAE market intelligence.
• Analyze RV exposure by brand, model, fuel type (ICE / Hybrid / EV) and fleet segment.
• Prepare RV scenario analysis (base, optimistic, downside) leveraging simulation and AI-based scenario tools.Data Science, AI & Advanced Analytics & Reporting

• Support the development, calibration and maintenance of predictive, prescriptive and generative AI models for RV forecasting, depreciation curves, portfolio risk analytics and predictive maintenance.
• Apply machine learning techniques (regression, gradient boosting, time series, clustering) to improve RV forecasting accuracy.
• Leverage generative AI and LLM-based tools (e.g., Microsoft Copilot, Claude) to accelerate data exploration, model improvements, documentation, report drafting and market intelligence synthesis.
• Contribute to data pipelines, feature engineering, data validation, model back-testing and MLOps workflows under the guidance of the Data Science team.
• Support model explainability (e.g. feature importance, SHAP, counterfactual analysis, Bayesian Inference, etc.) and robustness testing to meet governance requirements.
• Build and maintain automated dashboards for RV tracking, depreciation curve analysis and fleet health reporting using modern BI tools (Power BI, Tableau).
• Prepare monthly RV risk packs covering exposure, trends, variances and mitigation actions.
• Ensure data integrity across fleet management systems, valuation tools and remarketing platforms.Fleet Risk Management

• Monitor total fleet exposure (leasing, rental, subscription) against approved risk thresholds using automated alerts and AI-based anomaly detection.
• Identify high-risk models, over-aged stock, low-demand trims and vulnerable powertrains through data-driven segmentation.
• Support the design of risk-reduction actions such as early disposal, remarketing strategy changes, re-allocation across business units and pricing adjustments.
• Assist in stress testing the impact of economic factors including interest rates, inflation, regulatory changes, import duties and currency movements using scenario simulation tools.Market & Competitor Analysis

• Track UAE used-car market trends, auction performance and brand competitiveness, API-based data feeds and AI-driven market intelligence tools.
• Benchmark internal RV performance against competitors, leasing companies, OEM forecasts and market indices.
• Monitor the impact of EV adoption, ADAS technologies, warranty changes and lifecycle cost trends.Cross-Brand & OEM Engagement

• Support engagement with OEMs across all automotive brands on RV data, buy-back agreements, warranties and lifecycle assumptions.
• Assist in evaluating OEM incentive programs and their effect on RV stability using data-driven impact analysis.
• Prepare analytical support for negotiations on guaranteed buybacks, fleet deals or high-volume orders.Pricing & Product Support

• Provide RV input into leasing, rental and subscription pricing tools and validate margin implications.
• Support commercial teams in defining optimal contract lengths, mileage bands and service packages, leveraging AI-driven pricing optimization techniques.
• Contribute to lifecycle cost modelling for new mobility products and business cases.Used-Car Operations & Disposal Strategy

• Partner with used-car operations to analyze remarketing performance and minimize RV losses.
• Support recommendations on disposal channels (retail, wholesale, auction, export) using data-driven channel-mix optimization.
• Monitor time-to-market, margin performance and stock ageing.
• Track and forecast write-downs on used-car inventory using AI-supported provisioning models.Governance, Compliance & Policies

• Support adherence to the RV risk governance framework, model governance standards, policies and control procedures.
• Assist in preparing documentation for internal audit, external audit and financial reporting requirements (impairment, provisioning).
• Support model governance procedures for RV and AI/ML models, including version control, validation, monitoring and ethical AI considerations.Key Performance Indicators (KPIs)

• RV forecast accuracy vs. actual disposal outcomes

• Fleet depreciation variance monitoring

• Used-car margin performance

• Reduction in high-risk stock and ageing exposure

• Data quality, dashboard reliability and reporting timeliness

• Model performance metrics (accuracy, drift, back-test results)

• Contribution to pricing decisions and remarketing outcomes

• Effectiveness in leveraging AI tools to drive automation and productivity gains

Educational Qualification

• Bachelor's degree in Statistics, Mathematics, Economics, Data Science, Computer Science or a related quantitative field.

• Progress towards CFA, FRM or equivalent qualification is an advantage.

• Certifications in data analytics, machine learning, AI, cloud platforms (Azure, AWS, GCP) or RV-specific programs are a strong plus.

Work Experience

• 3-5 years of experience in data science, predictive modeling or financial risk analytics.

• Exposure to residual value forecasting, portfolio risk monitoring, machine learning or asset valuation strongly preferred.

• Hands-on experience deploying AI/ML models or automation workflows in a business setting is a plus.

• Understanding of the UAE automotive market and regional used-car dynamics, with prior experience in multi-brand automotive groups, leasing companies, banks or captive finance preferred.

Systems, Tools & Technical Skills

• Strong quantitative and analytical skills, including statistical analysis predictive modelling and financial modelling.

• Proficiency in Python and SQL programming language is a must.

• Familiarity with AI/ML frameworks (scikit-learn, TensorFlow, PyTorch) and cloud-based analytics platforms (GCP, Azure, AWS, Databricks) is highly desirable.

• Understanding MLOps concepts, version control (Git), model monitoring, back-testing, and reproducibility is a plus.

• Working knowledge of generative AI platforms and modern AI workflows, including Microsoft Copilot, OpenAI and Claude, with practical exposure to RAG, prompt engineering, agentic AI use cases, AI-assisted research, documentation automation and rapid prototyping.

• Familiarity with BI and data-visualization tools such as Power BI, Tableau, and modern data-preparation platforms (Alteryx, Power Query, notebooks).

• Solid understanding of automotive lifecycle economics, depreciation dynamics and used-car market behavior.

• Strong attention to detail, data integrity mindset and structured problem-solving skills.

• Effective written and verbal communication skills, with the ability to translate analysis into actionable insight for both technical and business audiences.

Competencies

• Analytical thinker with a risk-oriented mindset.

• Strong attention to detail and data integrity focus.

• Data-driven, AI-curious and tech-savvy, actively seeks to leverage new tools and technologies.

• Collaborative across commercial, finance, operations and IT.

• Ownership, accountability and delivery focus.

• Continuous learning mindset in a rapidly evolving AI and analytics landscape.

Languages

• Good written and verbal communication skills in English.