Data Science Manager

You are a forward-thinking Data Science Manager responsible for leading the development and deployment of machine learning models in the eCommerce Emerging Markets portfolio, focusing on forecasting, pricing, and customer analytics. Your role involves leveraging expertise in time series forecasting, pricing analytics, and GenAI/LLM technologies to enhance digital strategies, customer engagement, and overall business performance. Working in a high-impact, cross-functional capacity, you will collaborate with regional and global teams to deliver scalable data products that drive measurable business value. Your responsibilities include developing advanced models for demand forecasting, price optimization, and revenue management. This encompasses building and validating ML and DL algorithms such as ARIMA, Prophet, LSTM, DeepAR, LightGBM, and XGBoost. Additionally, you will work on developing LLM-based POCs and applying Agentic AI frameworks to address business challenges effectively. Creating customer churn, segmentation, and CLTV models will be crucial in optimizing customer engagement and retention while translating business issues into scalable ML solutions. In terms of engineering and deployment, you will deploy models using platforms like Databricks, AWS, and MLFlow and integrate them into cloud-based workflows. Automation of data pipelines for model training, scoring, and monitoring will be part of your responsibilities to ensure the use of clean, high-quality data inputs through robust data gathering and preprocessing. Collaboration with stakeholders from global and regional teams across Planning, Marketing, Finance, and Operations is essential. Your role will involve effectively communicating insights through compelling storytelling, dashboards, and decks. Mentoring junior data scientists and fostering a strong data culture within the organization are also key components. Driving the adoption of ML products by engaging and educating business users is another critical aspect of your role. To excel in this position, you must possess at least 6 years of hands-on data science experience in e-commerce, retail, or pricing analytics. A strong background in forecasting, pricing models, and causal inference is required. Demonstrated experience with LLMs, GenAI, or Agentic AI, as well as expertise in Python, SQL, PySpark, and libraries such as scikit-learn, TensorFlow, and Prophet, is essential. Cloud deployment experience on platforms like Databricks, AWS (S3, Lambda, SageMaker), or Azure is also necessary, along with experience in CI/CD, Docker, APIs, and production-grade ML systems. In addition to technical skills, strong soft skills are crucial for this role, including effective communication and storytelling abilities, collaboration, proactiveness, and confidence in driving cross-functional conversations. Being highly organized with excellent project management and execution abilities is also important. Bonus points if you have a background in consumer pricing, revenue management, or market mix modeling, as well as experience working with LLM tuning, prompt engineering, or LangChain/agent-based AI. Exposure to tools like Power BI, Adobe Analytics, Google Analytics, and Streamlit, or previous experience at an analytics consulting firm, would be advantageous. By taking on this role, you will have the opportunity to shape the data strategy of a globally renowned brand, work on cutting-edge AI and ML solutions at scale, collaborate with talent from digital, product, and analytics teams worldwide, and be part of a culture that values innovation, learning, and teamwork.,