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| Job Location | Bangalore |
| Education | Not Mentioned |
| Salary | Not Disclosed |
| Industry | IT - Software |
| Functional Area | General / Other Software |
| EmploymentType | Full-time |
This position requires a strong thought leader who can drive business decisions and issue resolution through collaboration. Proven ability to deliver results is a must. Individual must be able to effectively manage cross-functional partners that are internal and external to Accenture and Accenture s Clients. Ideal candidate will have to demonstrate excellent project management skills, strong communication with the ability to present findings to multiple levels. Experienced in managing and/or delivering capabilities and/or knowledge of SDLC in data management and systems configuration is a plus. The candidate should have some people management experience. Key Responsibilities: Develop methodologies to support Customer Analytical project execution for Retail / FMCG 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: 8-10 years of analytics overall experience, with hands on experience of predictive customer analytics in the CPG/Retail industry Exposure to US/ overseas Markets Strong Consulting and project management skills and demonstrated experience in managing teams across functions and geographies Prior experience of solutioning, shaping client opportunities in respective industry Must have Skills: Proficiency in one or more of analytical tools such as SAS product suite (Base Stat, E-miner, SAS EGRC), SPSS, SQL, KXEN and any other statistical tools such as R, Matlab etc. Advanced Excel including VBA and PowerPoint skills Ability to translate open ended business problems in analytical hypothesis and test the hypothesis leveraging various data sources Comfortable with techniques like logistic regression, segmentation / clustering, optimization, survival analysis Exposure to machine learning techniques like decision trees, random forest, gradient boosting, neural networks etc.,
Keyskills :
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