Details:

Description:

The primary work area will be in the realm of statistics, hypotheses testing, correlations & pattern recognition. The goal of this data scientist will be to look at various situations/scenarios/problems and apply different models to data to understand which model works with maximum efficiency & accuracy. Post testing, these algorithms will be deployed on the platform as one or more of the following: automated reports, automated analytics, custom reports etc. 

A lack of industry experience in this role should be compensated by a greater understanding of the data science realm: what models are out there currently? What models can be applied to a particular scenario? What direction should reporting & analytics take in the future? Are there more efficient ways of doing certain things we are already doing? Someone with a PhD level who has worked in finance or market research or process optimization or consumer theory etc. 

Top Line requirements across these roles include:

•Statistical testing: Regressions, correlations, hypotheses testing 

 •Clustering analyses

•Machine Learning techniques

•Predictive analytics: forecasting etc. 

•Data mining•Algorithm building 

•Decision tress & decision tree forecasting

Min. Qualification:

ug

Skills Required:

clustering, data mining, decision trees, forecasting, machine learning, regression, statistics