Details:

Key Responsibilities 

Utilize state of the art Machine learning and optimization algorithms for targeting customers to increase profitability, acquire new customers and increase retention. Propose and apply new algorithms for the same
Demonstrated analytical expertise, including the ability to synthesize complex data, effectively manage complex analyses, technical understanding of system capabilities and constraints

Develop methodologies to support Customer Analytical project execution for CMT / Telecom clients
Develop predictive analytics based solutions for o Customer Segmentation o Statistical Models across customer Lifecycle o Attrition / Cross-Sell / Upsell Propensity Models o Customer Lifetime Value o Pricing Analytics o Web Analytics
Apply appropriate techniques, such as exploratory data analysis, regression, bootstrapping, trees, cluster analysis, survival analysis and so on

Develop and articulate strategic recommendations based on rigorous data analysis 

Partner with client teams to understand business problems and marketing strategies 

Knowledge and skill requirements

1-3 years of analytics overall experience, including at least 1 year of quantitative analysis in the CMT/Telecom Industry
Exposure to Machine Learning with at least 1 year of practical experience in one or more approaches such as Random Forest, Neural Networks, Support Vector Machines, Gradient Boosting, Bayesian Networks, Deep Learning etc.
Hands on experience in Predictive analytics projects involving statistical modeling, customer segmentation etc.
Post Graduate degree in Statistics, Data Mining, Econometrics, Applied Mathematics, Computer Science or related field or MBA (Preferred)

Experience of working with US/ overseas markets is preferable SET YOURSELF APART: Key Competencies
Proficiency in two or more of analytical tools such as SAS product suite (Base Stats, E-miner, SAS EGRC), SPSS, SQL, KXEN and any other statistical tools such as R, MATLAB etc. (SAS/R are must)
Good knowledge of one of more programming language such as Python, Java, C++ is a plus
Advanced Excel including VBA and PowerPoint skills
Willingness to be flexible and work on traditional techniques as per business need
Consulting skills and project management experience is preferred
Excellent communication and interpersonal skills as well as collaborative, team player
Ability to tie analytic solutions to business/industry value and outcomes

Autonomous, self-starter with a passion for analytics and problem solving Must have skills: Hands on experience in Predictive analytics projects involving statistical modeling, customer segmentation etc. Good to have skills: Exposure to Machine Learning with at least 1 year of practical experience in one or more approaches such as Random Forest, Neural Networks, Support Vector Machines, Gradient Boosting, Bayesian Networks, Deep Learning etc. "

Min. Qualification:

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Skills Required:

data mining, deep learning, excel, java, machine learning, neural network, predictive modeling, python, r, random forest, sas, segmentation, spss, sql, statistical modeling, Support vector machine, VBA