Huimin 慧敏 Liu 刘's Linkedin Analytics

# Origin: Accidental management consultant # Flight-in-transit: Industry insight into ICT, TMT and multimedia services, and e-commerce, retail, FMCG, consumer durables, consumer services, and financial services sectors, having demonstrated analyses for industry market sentiments tracking and vendor benchmarking, VoC and CX surveys, and brand equity study, as well as consumer research across U&A study, conjoint modeling, new product / concept testing and pricing analysis. Data strategy design and data acquisition planning experience to facilitate UX and CX journey mapping for iterating existing data / products or build new data / products. Advanced data analytics skills with programming to build ML predictive statistical models such as logit, multivariate, and time-series regression modeling; and to code for text analytics in sentiment analysis. # Acclaimed Identify: Classic Data Scientist (still on data as-a-service?!) # Real Identity: Robotic Data Scientist (working secretly on data science as-an-algorithm) # Life’s Mission: 1. Working towards standardising for industry-specific solutions for what we have been doing for customising ML marketing science modelling solution by source of data and type of data contextualised to the customer’s business requirements by the nature of their business and industry. 2. Turning proprietary ML marketing science analytical models into XAI algorithms. To accelerate market traction of first targeted group of enterprise users at e-commerce, retail, and other consumer durables and consumer services companies, then going on to other industry verticals, such as blockchain analytics. 3. Turning proprietary ML marketing science analytical models into XAI algorithms. Introducing inductive-reasoning based ML models that should reinforce the validity of dependable models and add to the robustness of the results derived from inter-dependent models, so as to create XAI with emphasis on feature impact, prediction explanations and cluster insights, and to create A | B test experiments that can validate the stability of time-series models. MMF for XAI algorithms has been created. 4. In the future, we are looking to build an AI-powered product analytics platform with automatic features recommendation by interdependencies between marketing science modeling and PLG strategies created and to be validated, and data collection methods to be enhanced with privacy preserving ML with profit-sharing technology partner.