Senior Data Scientist

Design develop and deploy demand forecasting models using traditional and machine learning techniques like ARIMA XGBoost and LSTM Leverage Generative AI GenAI to enhance demand forecasting accuracy by simulating future demand scenarios and improving model predictions Implement dynamic pricing models using advanced algorithms to optimize pricing strategies based on demand predictions inventory levels and competitor data Analyze customer behavior by applying clustering algorithms and predicting customer lifetime value CLV with machine learning models to drive personalized pricing strategies Monitor evaluate and fine-tune model performance using metrics such as MAE RMSE and Precision Recall continuously improving model accuracy and robustness Apply MLOps practices including version control model deployment pipelines and automated testing to ensure seamless integration monitoring and scaling of models across environments Collaborate with cross-functional teams including marketing product and sales to ensure alignment between forecasting models and business objectives Deploy and scale forecasting and pricing models on Azure cloud platform leveraging CI CD pipelines and model monitoring tools for real-time performance tracking and proactive issue resolution Advanced machine learning model development and optimization skills.Expertise in Generative AI techniques for demand forecasting.Proficiency in MLOps practices and model deployment pipelines.Strong communication and collaboration abilities with cross-functional teams.

What Qualifies You For The Role:

• Master's degree in Statistics, Data Science, Machine Learning, Mathematics, Computer Science, or a related quantitative field.
• 10+ years of experience in data science, with at least 5+ years focused on demand forecasting, price optimization, and customer analytics.
• Strong hands-on experience with ARIMA, XGBoost, LSTM, and OR models.
• Proficiency in Python, SQL, Databricks, and cloud platforms (Azure, GCP).