Asst. Vice President - Next Gen-Specialist Group Job Details
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| Employer: | Citi Group | Job Ref No: | 11046459 | Job Title: | Asst. Vice President - Next Gen-Specialist Group | Sector: | Other | Sub Sector: | Other | Risk Type: | Other | Expertise: | Risk Manager | •PhD/Post Doc from a reputed institution in India (IISc, IIT's, ISI, IIM's etc) or Abroad in any advanced quantitative modeling oriented discipline including but not limited to Machine learning, Statistics, Marketing Science, Operations Research, Econometrics, Stochastic Finance, Distributed and parallel computing, Digital media analytics, etc. •Field of post graduation - Computer Science, Mathematics, Operations Research, Statistics, Econometrics, Management Science and related fields. Could be any graduate degree holder. •Strong academic record and publications in reputed journals or conferences. •3-5 years of post-PhD experience in the field of advanced quantitative techniques while working for leading global academic institutes or corporate innovation research labs or analytics organizations of large corporates or in consulting companies in analytics roles. •Sound knowledge and application in as follows : Stream/Skill Name (Any one)Competency Required (Any two or more of..) Advanced Quantitative Methods•Advanced statistical methods including complex multi-variate statistical methods, discrete choice modeling, conjoint based analysis •Machine learning including Bayesian methods, reinforcement learning, Neural networks, Support vector machines, Hidden Markov Models, relevance vector machines, Probabilistic/ Evidential Reasoning •Operations Research (Queuing, Markov Models, DEA, Integer Programming, Dynamic programming, Stochastic Programming, Game theory) EconometricsMacroeconomic modeling, Leading indicator analysis, Long term and near term Forecasting, Time series based methods, Bayesian multivariate regression methods, ARCH/GARCH/VAR models and other advanced regression methods, Mathematical economics, System dynamics, Stochastic control, Nonlinear dynamic models, etc. Prior practical industrial scale modeling exposure is a must. Digital Media and AnalyticsAdvanced quantitative methods relevant to modeling consumer experience in the digital world. Experience in web log mining for visitor segmentation, visitor behavior modeling, common path analysis, conversion analysis, abandonment analysis, promotion analytics, buzz analysis, sentiment analysis, social networking analysis etc is a must. Consumer behavior modelingLatent class models, Multivariate logit/probit/tobit models, Multinomial logistic models, Marketing mix modeling, Hidden Markov models, Conjoint methods, Market research and optimization methods. Prior experience in customer mindset modeling, customer loyalty, customer choice, brand equity, advertisements/promotion mix, etc is a must. Parallel and Distributed computing and problem solvingParallelizing existing traditional or modern (machine learning) based algorithms, Randomized algorithms, Simulations and Simulation based methods including Markov Chain Monte Carlo, parallel and distributed simulations, next gen optimization methods, etc. Knowledge of Hadoop/grid based programming for large scale problem solving is a must. Competency Requirements: •Passion and deep technical competency in quantitative methods and/or business analytics •Proven problem solving skills in industrial settings is a must •Proven ability in model building and application experience in data mining techniques and tools (SAS and/or other modeling packages like R, Matlab, Mathematica, ILOG etc) •Competent programming aptitude with excellent computation and data mining skills •Understanding of financial domain is preferred •Ability to translate and articulate technical thoughts and ideas to a larger audience including influencing skills with peers and senior management •Self motivated to continuously upgrade one's domain knowledge, keep abreast of latest developments in the field and evaluate its application in the business area on a consistent basis. •Exceptional commitment to stay focused in one's pursuit towards excellence with demonstrated results of the same. REducation Qualification Work Experience: •PhD/Post Doc from a reputed institution in India (IISc, IIT's, ISI, IIM's etc) or Abroad in any advanced quantitative modeling oriented discipline including but not limited to Machine learning, Statistics, Marketing Science, Operations Research, Econometrics, Stochastic Finance, Distributed and parallel computing, Digital media analytics, etc. •Field of post graduation - Computer Science, Mathematics, Operations Research, Statistics, Econometrics, Management Science and related fields. Could be any graduate degree holder. •Strong academic record and publications in reputed journals or conferences. •3-5 years of post-PhD experience in the field of advanced quantitative techniques while working for leading global academic institutes or corporate innovation research labs or analytics organizations of large corporates or in consulting companies in analytics roles. •Sound knowledge and application in as follows : Stream/Skill Name (Any one)Competency Required (Any two or more of..) Advanced Quantitative Methods•Advanced statistical methods including complex multi-variate statistical methods, discrete choice modeling, conjoint based analysis •Machine learning including Bayesian methods, reinforcement learning, Neural networks, Support vector machines, Hidden Markov Models, relevance vector machines, Probabilistic/ Evidential Reasoning •Operations Research (Queuing, Markov Models, DEA, Integer Programming, Dynamic programming, Stochastic Programming, Game theory) EconometricsMacroeconomic modeling, Leading indicator analysis, Long term and near term Forecasting, Time series based methods, Bayesian multivariate regression methods, ARCH/GARCH/VAR models and other advanced regression methods, Mathematical economics, System dynamics, Stochastic control, Nonlinear dynamic models, etc. Prior practical industrial scale modeling exposure is a must. Digital Media and AnalyticsAdvanced quantitative methods relevant to modeling consumer experience in the digital world. Experience in web log mining for visitor segmentation, visitor behavior modeling, common path analysis, conversion analysis, abandonment analysis, promotion analytics, buzz analysis, sentiment analysis, social networking analysis etc is a must. Consumer behavior modelingLatent class models, Multivariate logit/probit/tobit models, Multinomial logistic models, Marketing mix modeling, Hidden Markov models, Conjoint methods, Market research and optimization methods. Prior experience in customer mindset modeling, customer loyalty, customer choice, brand equity, advertisements/promotion mix, etc is a must. Parallel and Distributed computing and problem solvingParallelizing existing traditional or modern (machine learning) based algorithms, Randomized algorithms, Simulations and Simulation based methods including Markov Chain Monte Carlo, parallel and distributed simulations, next gen optimization methods, etc. Knowledge of Hadoop/grid based programming for large scale problem solving is a must. Competency Requirements: •Passion and deep technical competency in quantitative methods and/or business analytics •Proven problem solving skills in industrial settings is a must •Proven ability in model building and application experience in data mining techniques and tools (SAS and/or other modeling packages like R, Matlab, Mathematica, ILOG etc) •Competent programming aptitude with excellent computation and data mining skills •Understanding of financial domain is preferred •Ability to translate and articulate technical thoughts and ideas to a larger audience including influencing skills with peers and senior management •Self motivated to continuously upgrade one's domain knowledge, keep abreast of latest developments in the field and evaluate its application in the business area on a consistent basis. •Exceptional commitment to stay focused in one's pursuit towards excellence with demonstrated results of the same. R | Employment Type: | Full Time | Region/Country: | Asia / Pacific, India | City: | APAC-India | Address: | Post Date: | 05/20/2012 |
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