Profilbillede af mathstatconsulti
Flag for India Kolkata, India
Medlem siden 14. april 2014
1 Anbefalinger


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We have a member of 5 Statistician and Economists who are spearheading analytic solution development in Retail, CPG, Banking, insurance & Life science domain through marketing science research and econometric modelling implementation to solve business problems. Key Skills: Statistical modeling, Advance data meaning , Marketing Science Research and Econometric Estimation, Marketing analytics platform development, Advanced SAS Programming Domain Expertise: Consumer Packaged Goods and Retailing, Banking and Financial Services (Cards and Payments), Expertise: Multinomial regression model, survival analysis, Market Mix Models, Price and Promotional Effectiveness models, Demand forecasting, assortment optimization. Also we have expertise on SAS, R, Minitab and MS Excel. Total Years of Experience: 8+ years. We are seeking opportunities into advance statistical domain of your confidential company data and summarizing with a report or other Statistical Measure. If hired by you we will be responsible to complete the task within the stipulated time frame and with utmost confidence. Outsource me for your project and we promise to bring in the best output.
$20 USD/hr
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Senior Consultant

Jun 2005

Achieved high growth through delivery excellence & proficient customer communication skills resulting in manifold increase in multiple project revenue. Have been responsible for providing valuable business insights for clients across various domains. Have also been responsible for product development and refinement to suit specific client needs.


M.Stat , Optimization,Data Mining

2006 - 2008 (2 years)


Financial Risk Management (2010)



Improvising Dynamicity of ANN for Univariate Time Series Data

The arti cial neural network (ANN) is an advanced and resilient technique in many applications like prediction, clustering, classi cation, pattern recognition including forecasting. There have been immense applications of both traditional feedforward and feedback (recurrent) networks for forecasting of timedependent observations, be it short-term or long-term. Recently, Ghiassi and Saidane, 2005 [1] [2] proposed a dynamic architecture of ANN (IDANN), a primarily feed-forward network, to face the challeng


  • US English Level 1
  • Numeracy 1
  • Statistics 1


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