AddressLeadership Role - Data Science ( Retail Analytics ) : ( Only Females )
Must Have:
- In-depth knowledge of the retail sector, including understanding consumer behavior, market trends, supply chain dynamics, and the unique challenges faced by retail businesses
- Knowledge of Retail Analytics, including category management, shelf optimization, and sales performance analysis
- Experience in developing demand forecasting models, optimizing inventory management strategies
- Hands-on experience in the machine learning domains such as Regression, Classification, Unsupervised ML, Ensembles & Deep Learning
- Experience in Data analysis For e.g: data cleansing, standardization and data preparation for the machine learning use cases
- Experience in machine learning frameworks and tools (For e.g. scikit-learn, mlr, caret, H2O, TensorFlow,, Pytorch, MLlib)
- Advanced level programming in SQL and Python/Pyspark to guide teams
- Expertise with visualization tools For e.g: Tableau, PowerBI, AWS QuickSight etc.
- Ability to mentor and guide junior team members and act as an SME for all modeling and analytics deliverables
Nice to have:
- 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 ( e.g. AWS EKS, Kubernetes), Dockers and data pipeline orchestration (e.g. 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
