Manager Data Science - Finance

AlFuttaim; Dubai; On-site; AED 320,000 - 520,000; Full time

Job summary

Al-Futtaim in Dubai seeks a Manager Data Science - Finance to lead analytics initiatives across finance, risk, and performance. You will drive predictive modeling, financial analytics, KPI dashboards, and data science leadership to deliver actionable insights for strategic decisions.

The role requires 5 years in data science with a finance focus; you will mentor a team of data scientists, implement ARIMA/LSTM models, and translate complex results for business stakeholders while ensuring

Qualifications

• Bachelor's or MSc in a quantitative field with finance focus.
• 5 years of data science/analytics experience in finance.
• Proficiency in Python, SQL, and Databricks.
• Hands-on with scikit-learn, TensorFlow, PyTorch.
• Experience with ARIMA/SARIMA/Prophet and advanced predictive modeling.
• Experience with MLOps and Git.
• Experience with Matplotlib/Seaborn/Plotly.

Responsibilities

• Lead finance-focused data science projects and ML initiatives.
• Develop predictive models for residual value, credit scoring, delinquency, and collections.
• Create finance KPIs and dashboards; provide actionable insights for strategy.
• Mentor and manage a team of data scientists; communicate with stakeholders.

Skills

Python

SQL

Databricks

scikit-learn

TensorFlow

PyTorch

ARIMA

SARIMA

Prophet

LSTM

Gradient boosting

Ensemble methods

Neural networks

MLOps

Git

Matplotlib

Seaborn

Plotly

Time series

Forecasting

Statistics

Education

Bachelor's degree or MSc in Financial Analytics, Computer Science, or a related field

Tools

Python

SQL

Databricks

Job description

Manager Data Science - Finance

Location: Dubai, United Arab Emirates

Industry: Automotive

Function: Mathematical-Statistical Research

Experience: 5 years of experience in data science and analytics with a strong focus on finance

Job Type: Full-time

Al-Futtaim is hiring a Manager Data Science - Finance in Dubai, United Arab Emirates to lead advanced analytics and machine learning initiatives that strengthen financial performance and risk management. The role combines predictive modeling, financial analytics, KPI and dashboard development, and data science leadership to deliver actionable insights for strategic decision-making. Key areas include residual value prediction, credit scoring, delinquency forecasting, collections optimization, anomaly detection, and financial stress testing.

Country: United Arab Emirates

City: Dubai

Industry: Automotive

Function: Mathematical-Statistical Research

Salary: Not disclosed

Gender: No Preference

Candidate Nationality: Not specified

Job Type: Full-time

The Manager Data Science - Finance will lead the execution of finance-focused data science projects and oversee a team of data scientists responsible for transforming complex financial information into practical analytical solutions. The position requires strong expertise in statistical modeling, machine learning, financial analytics, and data visualization. Success will be measured through the delivery of predictive use cases, comprehensive finance dashboards, and recurring insights that support financial and risk-related decisions.

Predictive Modeling

• Implement predictive models covering residual value prediction, credit scoring, delinquency prediction, and collections optimization.
• Apply advanced analytics to improve financial performance and strengthen risk management.
• Use appropriate statistical and machine learning techniques to develop reliable predictive solutions.
• Deliver at least two successful predictive modeling use cases.
• Apply ARIMA and LSTM networks where appropriate for predictive analytics.
• Utilize gradient boosting, ensemble methods, and neural networks to address financial modeling requirements.

Financial Insights and Analysis

• Apply time series decomposition to identify meaningful patterns within financial data.
• Use anomaly detection techniques to identify unusual financial behavior or performance.
• Conduct stress testing to support financial analysis and risk assessment.
• Generate three actionable financial insights each month to support business decisions and strategy.
• Translate analytical findings into clear recommendations for relevant stakeholders.
• Communicate complex technical concepts effectively to non-technical audiences.

KPI and Dashboard Development

• Create financial KPI metrics using appropriate statistical techniques.
• Develop risk dashboards that provide actionable information to stakeholders.
• Build and maintain three comprehensive finance-related dashboards.
• Apply data visualization techniques to communicate complex financial information clearly.
• Ensure analytical outputs remain aligned with relevant business objectives.

Data Science Leadership

• Lead a team of data scientists in delivering finance-focused analytics initiatives.
• Guide the execution of machine learning and advanced analytical projects.
• Maintain focus on practical business outcomes when developing analytical solutions.
• Support effective communication between technical teams and business stakeholders.
• Promote structured implementation of analytical models and data science use cases.

Technical Skills

• Python
• SQL
• Databricks
• scikit-learn
• TensorFlow
• PyTorch
• ARIMA and SARIMA
• Prophet
• LSTM networks
• Gradient boosting and ensemble methods
• Neural networks
• MLOps
• Git
• Matplotlib
• Seaborn
• Plotly
• Statistical analysis and financial modeling
• Time series decomposition
• Anomaly detection and stress testing

What Qualifies You for the Role

• Bachelor 's degree or MSc in Financial Analytics, Computer Science, or a related field.
• 5 years of experience in data science and analytics with a strong focus on finance.
• Proficiency in Python, SQL, and Databricks.
• Hands-on experience with machine learning libraries and frameworks including scikit-learn, TensorFlow, and PyTorch.
• Practical knowledge of ARIMA, SARIMA, Prophet, and advanced predictive modeling techniques.
• Hands-on experience with MLOps and Git.
• Experience with data visualization tools including Matplotlib, Seaborn, and Plotly.
• Strong statistical and analytical capabilities for financial analysis and modeling.
• Ability to communicate analytical findings and complex technical concepts to non-technical stakeholders.