Responsibilities:
65% of Time
Statistical forecasting :
- Pre-process and cleanse the input data for outliers and imputation of zero ship periods
- Univariate time series modeling using exponential smoothing and Box Jenkins methods for very large data sets at SKU, warehouse and Customer level in weekly and monthly buckets
- Multivariate modeling incorporating external and causal factors into forecasting
- Leverage machine learning models (Support vectors, Ensembles - Random forest, Gradient boosting etc.) & deep learning (Recurrent Neural network (LSTM) etc.) to generate best in class forecast accuracy.
- Exception handling and alert management to effectively review and manage forecasting KPIs above-defined targets
- Long-term forecasting incorporating strategic inputs from marketing, finance, operations, etc.
- Effectively deploy results to stakeholders using predictive, prescriptive analytics and data visualization
25% of Time:
Segmentation & demand planning analytics :
- Generate forecast for New Items using like item modeling/ machine learning approaches
- Perform descriptive & diagnostics analysis on historical demand & shipment data
- Forecast Visual analytics, scenario planning, model diagnostics
- Build a solution framework for segmented demand planning by leveraging Clustering methods
- Distance matrix, Dimensionality reduction, K-means, DBSCAN, etc.
- Enhance Demand disaggregation methodology and accuracy
10% of Time :
Training / Knowledge :
- Working on Individual development plans
- Interpersonal effectiveness
- Ability to influence across teams/boundaries
- Good written/oral communication
- Learning Agility
- High level of analytical skills, functional competence in the area of Demand management, Ability to influence without power, Good interpersonal skills, etc.
Shift: 1.30 PM to 10.30 PM
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