Data Science & Risk Analyst

About the Role
This role focuses on the integration of strategy, data science, and risk management within the automotive industry, specifically targeting residual value (RV) forecasting and analysis. It encompasses a wide array of responsibilities including the development of predictive models, market analysis, cross-brand interactions, and compliance with governance standards.

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 modeling 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 aging.
• 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 aging 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 modeling, and financial modeling.
• 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.