Data Scientist Manager

As a Senior Data Scientist specializing in analytics, Generative AI, and automation within the Business Intelligence team, reporting to the Head of Automation, your role will encompass a variety of key responsibilities to drive actionable business insights and support strategic planning in the FMCG domain. Key Responsibilities: - Build and maintain dashboards for sales, distribution, and trade promotion performance, covering various regions and channels. - Perform exploratory analysis to identify trends, growth opportunities, and areas of concern for leadership. - Develop KPI scorecards and automated reporting pipelines to enhance data accessibility and reduce manual efforts. - Develop Gen AI solutions using LLMs like GPT, Claude, Gemini, or open-source models for tasks such as automated report generation and document summarization. - Utilize ML techniques such as classification, regression, clustering, and NLP to address business challenges like customer segmentation and churn prediction. - Implement RAG-based pipelines and explore AI agent frameworks to automate analytical workflows effectively. - Create demand forecasting models for sales prediction and inventory planning. - Construct financial models covering P&L analysis, revenue forecasting, and budget planning in collaboration with the Finance team. - Support strategic initiatives with scenario analysis and data-driven recommendations as part of the annual operating plan. - Identify and automate repetitive reporting and data processing tasks using Python, SQL, and tools like Power Automate or Airflow. - Establish anomaly detection alerts to proactively identify issues in sales, inventory, or financial data. - Build and maintain ETL pipelines for ensuring clean, timely, and reliable data flows across the BI ecosystem. Required Skills: - Strong proficiency in Python (Pandas, Scikit-learn, Statsmodels) and SQL for data analysis, modelling, and automation. - Hands-on experience in building and deploying ML models including supervised/unsupervised learning, time-series forecasting, and NLP. - Working knowledge of LLM APIs, RAG architectures, and frameworks like LangChain or LlamaIndex for Generative AI tasks. - Proficiency in Power BI for creating executive-level dashboards and data storytelling. - Familiarity with at least one cloud platform (AWS, Azure, or GCP) for data storage, processing, or ML deployment. - Understanding of sales analytics, demand planning, distributor performance, and trade dynamics in the FMCG domain. - Ability to effectively communicate complex analysis to both technical and business audiences. Valuable to Have: - Experience with RPA tools like UiPath or Power Automate, and familiarity with workflow orchestration tools such as Airflow or dbt. - Exposure to MLOps practices including model versioning, monitoring, and retraining pipelines. - Prior experience with cloud data warehouses like Snowflake, BigQuery, or Redshift. Qualifications: - Bachelors or Masters degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or related fields. - 5-6 years of experience in data science, analytics, or related roles with demonstrable business impact. - 1-2 years of hands-on experience with Generative AI tools and technologies. - Relevant certifications in ML, AI, or Cloud are advantageous but not mandatory. As a Senior Data Scientist specializing in analytics, Generative AI, and automation within the Business Intelligence team, reporting to the Head of Automation, your role will encompass a variety of key responsibilities to drive actionable business insights and support strategic planning in the FMCG domain. Key Responsibilities: - Build and maintain dashboards for sales, distribution, and trade promotion performance, covering various regions and channels. - Perform exploratory analysis to identify trends, growth opportunities, and areas of concern for leadership. - Develop KPI scorecards and automated reporting pipelines to enhance data accessibility and reduce manual efforts. - Develop Gen AI solutions using LLMs like GPT, Claude, Gemini, or open-source models for tasks such as automated report generation and document summarization. - Utilize ML techniques such as classification, regression, clustering, and NLP to address business challenges like customer segmentation and churn prediction. - Implement RAG-based pipelines and explore AI agent frameworks to automate analytical workflows effectively. - Create demand forecasting models for sales prediction and inventory planning. - Construct financial models covering P&L analysis, revenue forecasting, and budget planning in collaboration with the Finance team. - Support strategic initiatives with scenario analysis and data-driven recommendations as part of the annual operating plan. - Identify and automate repetitive reporting and data processing tasks using Python, SQL, and tools like Power Automate or Airflow. - Establish anomaly detectio