Job Description:
• Develop advance statistical forecasting models in Python to improve forecast accuracy (variance and MAPE).
• Work closely with business customers to identify and address forecasting issues and opportunities.
• Analyze forecasting metrics to uncover trends and find root causes of forecast inaccuracy.
• Build metrics, reports and dashboard to analyze key inputs to the forecasting system and key outputs including forecast accuracy and variance, and impact on downstream business metrics.
• You are comfortable presenting your findings to large groups, both internally and externally.

Basic Qualification:
• MBA Operations / Finance or M.S. Data Science from a top tier business school.
• 4-5 years of total experience in advance data analytics out of which at least years 2 years should be with a top tier consulting firm.
• Experience with statistical forecast modeling in Python.
• Exceptional quantitative and analytical abilities – Advance Excel, Access and SQL skills.
• Deep knowledge of statistics and experience applying SPSS, SaaS and other analytical tools.
• Experience in designing and building data infrastructure / automated reporting tools.
• Ability to build the framework for the analyses and to drive decisions with the derived insights.

Preferred Qualification:
• MBA - Finance and Operations/ Phd.Data Science from a top tier business school.
• A total of 5-6 years of experience in advance data analytics out of which 3-4 years should be with a top tier consulting firm.
• Experience with statistical forecast modeling in Python.
• Experience handling terabyte size datasets.
• Knowledge and direct experience using BI reporting tools (Tableau, Business Objects, Cognos, Pinnacle, MicroStrategy, etc.).
• Experience with statistical forecast modeling in Python.
• Strong ability to communicate (written and verbal) complex analyses and conclusions in clear, simple ways.
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