Mu Sigma is a category defining Decision Sciences and Big Data analytics company helping enterprises institutionalize data-driven decision making. Mu Sigma’s unique interdisciplinary approach and cross-industry learning drive innovation in solving high-impact business problems across marketing, risk and supply chain. With over 3000 decision scientists and experience across...
Mission: To enable businesses to institutionalize data-driven decision making.
- Overview |
Analytics and data-driven decision making have been well recognized as a distinctive competitive advantage in a world of Big Data and increasing business complexity. Organizations are challenged with scaling the use of analytics and making it an integral part of all business decisions. Mu Sigma addresses this critical need and enables organizations to institutionalize analytics and Decision Sciences in a sustainable manner.
Creating Decision Sciences talent is not a one-time effort, but a continuous process. This talent needs to be groomed and nurtured in an environment where art and science can exist in harmony.
Building an analytically strong organization that is focused on helping people make better, faster, data-driven decisions, wouldn’t have been possible without a holistic view of Decision Sciences.The future will witness the notion of analytics evolving into Decision Sciences encompassing Math + Business + Technology + Behavioral Sciences.
To achieve our vision of building the world’s largest Decision Sciences organization, we are focused on creating Decision Sciences soldiers, captains and generals.
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1 Mu Sigma Salary
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Trainee Decision Scientist at Mu Sigma (student candidate)
Accepted Offer – Interviewed in Jul 2014 – Reviewed 2 weeks ago
Interview Details Interview consisted of 4 rounds.
1. Aptitude (15 questions with negative marking)
2. Video Synthesis/ Problem Solving (Finding O/P of a simple pseudo-code)
3. Group Discussion (Business case study on selling merchandise of an IPL team)
4. Personal Interview (General questions) – Full Interview
The GD case study question was unexpected. It wasn't difficult though as I had some knowledge about it. – Answer Question