Data Science & Risk Analyst

Role Overview

Data Science & Risk Analyst at AWR Group. The role supports the Director – Data Science & Risk Management in executing the Group's Residual Value (RV) risk framework across all automotive brands and multiple mobility business units, including leasing, rent-a-car, subscription services, and used-car operations.

Company Overview

AW Rostamani Group is a leading multi-sector family business in the Middle East with over seven decades of legacy. Operations span automotive, real estate, retail, lighting solutions, travel, logistics, agritech and sustainable packaging. The Group serves over 155,000 customers and 24,000 businesses annually, supported by more than 3,000 employees.

AWR Automotive, a flagship vertical of AW Rostamani Group, has shaped transportation in the Middle East for over five decades. It represents leading global brands including Nissan, INFINITI, and Renault exclusively in Dubai and the Northern Emirates, while Zeekr, Chery, and Smart are offered across the UAE. The company drives innovation through flexible mobility solutions including its homegrown brands Shift and Subscribe Me.

Role Purpose

The Data Science & Risk Analyst focuses on analytical, modelling and reporting activities required to forecast residual values, monitor portfolio risk exposure, track used-car market dynamics, and provide data-driven insights that support RV setting, pricing, reserve adequacy and remarketing decisions. The role actively leverages AI, machine learning and modern data tools to enhance forecasting accuracy, automate reporting, and accelerate insight generation while working cross-functionally with Finance, Commercial, Fleet, Data Science and Used-Car Operations teams to protect asset value and safeguard portfolio profitability.

Key Responsibilities

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 and 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) 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 via 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.

Qualifications & Experience

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

Skills & Competencies

• Strong quantitative and analytical skills, including statistical analysis, predictive modelling and financial modelling.
• Proficiency in Python and SQL programming languages 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 of 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.
• Analytical thinker with a risk-oriented mindset.
• 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.
• Good written and verbal communication skills in English.

Additional Information

Key Performance Indicators

• 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