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Head Of Data Scientists Resume

SUMMARY

  • Marketing/Digital Marketing Analytics, Marketing Mix Modeling, Customer Life Time Value Estimation, Customers Behavior Prediction, Risk Analysis, Nature Language Processing
  • E - commerce support, Online / email Recommendation
  • Dynamic Pricing, Stochastic Prediction & Optimization
  • Deep Learning, Multilayer Perceptron, Convolutional Network, Auto Encoders, Restricted Boltzmann Machines, Deep Belief Networks, Tensorflow, Natural Language Processing / Text Mining
  • Machine Learning & Reinforcement Learning (Random Forest, Support Vector Machine, Gaussian Mixture Models, Markov Chain Monte Carlo, Bayesian Network, Hidden Markov Model, Conditional Random Field, Gaussian Process, Bayesian Optimization, Latent Dirichlet Allocation, Latent Class Analysis, Boosting, Bagging, Genetic Algorithm, etc.)
  • Statistics (Econometrics, Bayesian, Survival Analysis, Partial Least Square, GLM, logistic regression, factor analysis/principle component analysis, ARIMA/GARCH, path analysis, structure equation modeling, ordinary least square / maximum likelihood / EM)
  • Big Data and Cloud Computing, Amazon Web Services (AWS) / EMR / EC2 / S3 / VPC, Hadoop / Apache Spark / MLlib / Hive / Pig
  • Python, R, Java, SAS (Base, IML, ETS, Macro and Enterprise Miner programming), Oracle, MS SQL Server

PROFESSIONAL EXPERIENCE

Head of Data Scientists

Confidential

Responsibilities:

  • Build up and lead data scientist team to support Marketing, Digital Marketing, E-commerce and Pricing: road map, analytical resource planning, computing architecture, project management and hand on modeling
  • Communicate with top management and internal customers: project initiation, project coordination, model development and presentation
  • Lead and hands on major projects (samples):

Lead Data Scientist

Confidential

Responsibilities:

  • Leading all analytical effort to support Customer Organization, establishing, documenting, distributing, defending and analyzing all customer forecasts and supporting analyses, Marketing mix modeling, ROI by marketing activities, optimizing marketing spending, analyzing marketing metrics for identifying effect-cause relationships between financial outcomes and marketing actions to raise effective return on investment of marketing campaigns
  • Social media analysis, sentiment analysis, information extraction from call in audio records
  • Quantitatively supporting other business units, stochastic forecasting of gas and electricity day ahead load, long term and short term electricity and gas price prediction, optimization of energy efficiency solutions for individual customers - statistical modeling of energy consumption, model calibration, simulation and stochastic optimization
  • Managing analytical resources including personnel, data, application, internal/external supporting units, etc.
  • Communicating with customers, working as liaison between quants and business units: provide business view from analytical perspective and translate business needs to analytical goals
  • Assisting in developing surveys and defining focus groups to capture detailed customer and market data, conducting quantitative market research and analysis for determining brand perceptions, understanding customer needs, evaluating market penetration and analyzing competitors

Sr. CRM Analyst

Confidential

Responsibilities:

  • Leading analytical effort to evaluate & reduce the risk of customer account closure, predict customer shopping behavior, explore new way to better customer relationship management, measure & improve customer life value, providing analytics reports on key shopping patterns along with recommendations for enhancing marketing and driving more sales (department cross shopping patterns, coupon data, marketing strength and campaign channel)
  • Marketing mix modeling, measuring / estimating ROI by marketing activities, optimizing marketing spending based on marginal contribution of different marketing channels
  • Support e-commerce - Belk.com with optimization and statistics modeling to identify business opportunities, cost-saving opportunities and challenging existing business strategies
  • Teamwork with IT and external agencies to integrate customer information from multiple databases in order to improve communications at the customer level and make marketing more targeted
  • SAS (Base, ETS, Macro and Enterprise Miner), Oracle Data Warehouse, SQL
  • Selected projects:

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