Data Science

 Key Analytical Focus Areas:

o Customer segmentation and clustering using demographic, behavioural, and transactional data

o Marketing Mix Modeling (MMM) and campaign analytics to assess marketing effectiveness and ROI

o Price and profit optimization models across products and segments

o Conjoint analysis and product affinity modeling for innovation and customer preference alignment

o Demand forecasting, dynamic pricing, and elasticity modeling

 Expertise in Advanced ML & Statistical Methodologies:

o Experience with techniques such as Random Forest, XGBoost, SVM, Gradient Boosting, Time Series Forecasting, Logistic Regression, K-Means Clustering, Hierarchical Clustering, Lasso/Ridge Regression, PCA, Survival Models, and Ensemble Methods

o Familiarity with deep learning models for NLP, image analysis, and unstructured data processing

 AI Engineering & Emerging Platforms:

o Exposure to AI engineering principles for scalable model deployment using CI/CD and MLOps pipelines

o Hands-on experience or understanding of agentic platforms, LLM-based orchestration, or intelligent agent frameworks for task automation and knowledge management

o Working knowledge of integrating ML solutions into production environments and performance optimization

 Mandatory Tools Experience:

o Microsoft Office: Proficient in Microsoft Excel for advanced data analysis and financial modeling, and Microsoft PowerPoint for creating impactful presentations and visualizing data insights

o Python/R: Proficiency in Python or R for data manipulation, statistical analysis, and machine learning

o SQL: Strong command over SQL for data querying and management

o Tableau/Power BI: Experience in data visualization using Tableau or Power BI to communicate insights effectively