End to end forecast process design which includes development of data extraction and transformation logic & build and deployment of predictive models.
Use of adv. analytics techniques and machine learning algorithms to forecast key business metrics.
Building Monthly, Bi-Monthly & Quarterly Revenue forecasting models for product groups, product sub-groups and profit centers using Regression Modeling,
Time Series, ARIMA, GBM, decision Tree, Random Forest, Neural Net etc.
Variance analysis for all the forecast models to help business understand the root causes behind the variation. Use the learning to improve the overall forecasting process.
Proactively anticipates and prevents problems. Devises, facilitates buy-in, makes recommendations and guides implementation of corrective and/or preventive actions for complex issues that cross organizational boundaries and are unclear in nature.
Develops innovative and effective approaches to solve predictive analytics problems and communicates results and methodologies..
Collaborate with subject matter experts to enhance predictive models.
Preparation of all the supporting documents and reports.
Strong SAS knowledge
4-8 + years of relevant work experience in machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, GBM, etc.
Must to have experience with common statistical tool, such as R and Python. Excellence in at least one of these is highly desirable
Great communication skills
Good applied statistics skills, such as distributions, statistical testing, regression, etc.
Good scripting and programming skills