Senior Data Scientist Job in Dubai, United Arab Emirates

Position Overview:

We seek an experienced Senior Data Scientist to join our team and lead projects focused on demand forecasting, price optimization, and customer analytics. In this role, you will leverage machine learning models to predict demand, optimize pricing strategies using dynamic pricing techniques, and analyze customer behavior to inform key business decisions. Your expertise will be critical in enhancing inventory management, refining pricing strategies, and boosting overall customer satisfaction, directly contributing to the company’s growth and profitability.

Key Responsibilities:

• Strategic Problem Solving: Collaborate with stakeholders to identify and address business challenges through data-driven insights.
• Stakeholder Communication & Management: Effectively communicate findings, progress, and recommendations to stakeholders across various functions.
• Model Development & Deployment: Design, develop, deploy, and maintain machine learning models for demand forecasting, price optimization, and customer analytics.
• AI Innovation: To enhance accuracy, identify opportunities to integrate innovative AI solutions, including Generative AI (GenAI), into demand forecasting and pricing models.
• Forecasting Models: Develop demand forecasting models using techniques like ARIMA, XGBoost, and LSTM to predict future demand patterns.
• Pricing Optimization: Implement dynamic pricing models that adjust pricing based on demand predictions, inventory levels, and competitor data.
• Customer Behavior Analysis: Apply clustering and predictive models to understand customer behavior and predict customer lifetime value (CLV) for personalized pricing strategies.
• Model Performance: Monitor, evaluate, and improve model performance using metrics such as MAE, RMSE, and Precision/Recall, ensuring continuous model enhancement.
• Model Explainability: Use tools like SHAP and LIME to explain machine learning model predictions and increase stakeholder trust in model results.
• MLOps Practices: Ensure seamless integration, deployment, and monitoring of models across environments by implementing MLOps practices, such as version control, automated testing, and deployment pipelines.
• Collaboration: Work closely with cross-functional teams (marketing, product, and sales) to align forecasting models with broader business objectives.
• Cloud Deployment & Scaling: Deploy and scale models on the Azure cloud platform, utilizing CI/CD pipelines and model monitoring tools for real-time tracking and issue resolution.

Key Skills & Qualifications:

• Experience: Minimum of 10 years of experience in data science, with at least 5 years of experience in developing and deploying solutions related to demand forecasting, price optimization, and customer analytics.
• Industry Knowledge: Prior experience in Retail, FMCG, or Automotive industries is essential.
• Machine Learning Expertise: Hands-on experience with ARIMA, XGBoost, LSTM, and classification models for price elasticity and customer behavior prediction.
• Generative AI: Proficiency in applying Generative AI (GenAI) techniques for demand forecasting and optimization tasks.
• Programming Skills: Proficiency in Python, SQL, and cloud platforms (Azure, GCP), as well as familiarity with data processing frameworks like Spark.
• MLOps Experience: Strong knowledge of MLOps practices, including version control, automated testing, deployment pipelines, and model monitoring in production.
• Cloud & Data Pipeline Management: Expertise in deploying and managing models on cloud platforms, managing large-scale data pipelines, and integrating real-time data for demand and pricing optimization.
• Model Tuning & Monitoring: Extensive experience with feature engineering, model tuning, and evaluating model performance using metrics like MAE, RMSE, and R².
• Communication Skills: Strong ability to collaborate and communicate effectively with cross-functional teams and stakeholders to drive impactful data-driven decisions.
• Data Security & Scalability: Familiarity with best practices for data security, scalability, and model interpretability.
• Deep Learning Frameworks: Hands-on experience with PyTorch and TensorFlow is preferred.

About the Team:

You will report directly to the Data Science Lead and work with a dynamic, cross-functional team focused on delivering cutting-edge data science solutions.