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Job Description

• A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics
• We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology
• We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge
• As part of our Analytics and Insights Consumption team, you'll analyze data to drive useful insights for clients to address core business issues or to drive strategic outcomes
• you'll use visualization, statistical and analytics models, AI/ML techniques, Modelops and other techniques to develop these insights

• In-depth understanding of the CPG industry, including knowledge of market trends, consumer behavior, supply chain dynamics, and retail operations
• Familiarity with pricing strategies to optimize pricing models, promotions, and discounts
• Knowledge of retail analytics, including category management, shelf optimization, and sales performance analysis
• Experience in developing demand forecasting models and optimizing inventory management strategies
• Hands-on experience in developing price elasticity models using Log-Log, Log-Linear, Bayesian Regression algorithms as well as machine learning algorithms, like Random Forest, XGBoost. Also be familiar with Unsupervised ML, Ensembles & Deep Learning
• Experience in Data analysis For eg : data cleansing, standardization and data preparation for the machine learning use cases
• Experience in machine learning frameworks and tools (For eg scikit-learn, mlr, caret, H2O, TensorFlow,, Pytorch, MLlib)
• Advanced level programming in SQL and Python/Pyspark to guide teams
• Expertise with visualization tools For eg : Tableau, PowerBI, AWS QuickSight etc

• Experience in building ML models in cloud environments (At least 1 of the 3: Azure ML, GCP s Vertex AI platform, AWS SageMaker)
• Working knowledge of containerization ( eg AWS EKS, Kubernetes), Dockers and data pipeline orchestration (eg Airflow)
• Experience with model explainability and interpretability techniques
• Multi-task and manage multiple deadlines. Responsible for incorporating client/user feedback into the Product
• Ability to think through complex user scenarios and design simple yet effective user interactions
• Good Communication and presentation skills

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