Data Scientist Machine Learning

Cover Letter

Key Professional Strengths

*). Nearly 20 years of hands-on predictive modeling, quantitative analytics (SAS, Python, SQL), 27 years if including academic research and publications in graduate schools using predictive models.

2). Five years of team management, 15 years of team mentoring.

3). Strong research results presentation skills (to non-research audiences, up to all levels of executives).

4). Solid understanding of common market research vendor practices and techniques.

Key Analytical Areas (both B2B and B2C)

Key business world analytics experiences cover various areas such as predictive modeling, machine learning models, CRM measurement, customer acquisition, customer satisfaction, loyalty, market sizing, segmentation, inventory mix optimization, head count staffing, process optimization, A/B testing, product naming, product development, product pricing, brand equity tracking, brand messaging and brand positioning.

Sincerely,

Terry Pan, PhD

Segment Strategist/Head Data Scientist, Discount Tire

811 Novalis St

Nolensville TN 37135

Cell: 502-***-****

Email: ************@*****.***

Terry Pan, PhD

811 Novalis St, Nolensville TN 37135

Email: ************@*****.***, Cell: 502-***-****

EXPERIENCE

03/2021-present Discount Tire, Scottsdale, AZ

Segment Strategist/Head Data Scientist

Personally lead or supervise major complex data science or modeling projects, mentor junior data scientists, communicate complex modeling insights to and influence decisions by all level of senior management up to C-level officers.

Personally lead, execute store operation optimization project to improve customer experience (Algorithm has been implemented across all 1000+ stores)

Personally lead and manage price optimization project generating cumulative $250M+ lift in revenue

05/2015-03/2021 Bridgestone Americas Tire Operations, Nashville, TN

Principal Data Scientist

Personally lead or supervise major complex projects, mentor junior data scientists, communicate complex modeling insights to and influence decisions by all level of senior management up to C-level officers.

Analytics projects cover all areas of the business: Forecasting, Supply Chain, Inventory, Pricing, Operations, Marketing, Real Estate, HR, Merchandizing, Manufacturing Process, etc. Various projects have generated tens of millions in incremental profit or expense savings, often in a single project.

Sample successful advanced analytical projects include:

oRetail store inventory mix prediction for every store and product, generating tens of million dollars incremental revenue per year

oNew store revenue prediction model with the potential to generate 50+ million dollars in incremental revenue per year

oInter store revenue cannibalization prediction that allows simulation of revenue impact on any point of the map within the United States, with the potential to avoid millions of wasted capital spending in one single nonperforming store. Impact in the tens of millions if multiple nonperforming stores are avoided

oCustomer acquisition models for targeted customer relationship management with the potential to generate tens of millions incremental revenue per year

oSales forecast for thousand of products to inform manufacturing schedules for both the short and long term

oManufacturing process flow forecast and optimization that results in 50-80% reduction in operational downtime (which in turn increase production output)

oHighly accurate company performance forecast to inform business planning and intervention with the potential impact in the millions of dollars

oDozens of A/B testing projects in marketing, operations, pricing, staffing that have generated tens of million dollars in incremental profit each year

12/2012 – 12/2014 Sears Holding Company (a major big box retailer), Chicago, IL

Director of Pricing Analytics (01/2014 –12/2014)

Explore ad hoc analytical projects to support pricing execution and drive incremental margin

Build price elasticity models, manage A/B testing strategy and measurement for consumer electronics business unit ($2 billion revenue) in various marketing channels (online, in-store, circular, etc.)

Manager of CRM Analytics & Measurement (12/2012 - 01/2014)

Led both internal and offshore modeling teams to develop customer purchase propensity models, drive incremental revenue and margin via testing & learn campaigns

Built 30+ purchase propensity models with my team, with the models impacting $200 million annual revenue and generating 20%+ lift in offer redemption, revenue and margin metrics for select offers in targeted marketing channels

Helped devise strategy for personalization & optimization of 100 million+ marketing offers to drive incremental revenue & margin in marketing channels such as POS, email, online, & direct mail (1%-20% lift observed)

Managed external consultant for technical consulting engagement, acquired advanced level SQL skills in select area

09/2011 – 12/2012 Caesars Entertainment Corp (the largest casino operator), Las Vegas, NV

Sr. Analyst, BI Advanced Analytics

Built pricing models, leveraged dynamic pricing tool to optimize hotel room pricing while maximizing revenue ($15+ million potential incremental revenue per year within a team of four)

Built forecasting models to forecast industry trend, results well received by C-level officers and impacted many corporate capital/budget decisions ($100 million to $1 billion dollar decisions)

Built predictive models to gain insights on customer behavior, then recommend actions to drive EBITDA ($10+ million incremental revenue potential per year)

Conducted market intelligence analysis in support of decisions on billion-dollar corporate developmental project

Select results presented to and well received by corporate CEO, CMO, CFO, regional presidents and SVPs

10/2010 – 09/2011 Service Management Group (a customer experience research vendor), Kansas City, MO

Senior Research Analyst

Served as SME (Subject Matter Expert) for consumer panel research, branding research projects from design, data collection, analysis to reporting

Sample clients include Payless, JC Penney, Star Bucks, Jack in the Box, Advance Auto Parts, Burger King, etc.

04/2008 – 10/2010 Illuminas Global (a boutique consulting firm), Austin, TX

Senior Manager of Analytics

Led advanced modeling and ad hoc analyses for 100+ brand tracking, customer insights & product pricing studies, generated insights impacting hundreds of millions in client revenue

Sample clients include Cisco, AMD, Intel, Auto Desk, Time Warner Home Video, Oracle, etc.

07/2004 – 01/2008 Pacific Institute for Research & Evaluation (applied research vendor), Louisville, KY

Associate Research Scientist (10/2005 - 01/2008)

Senior Research Analyst (07/2004 - 10/2005)

Built advanced statistical models for program effectiveness evaluation studies in public health area

Accumulated 13 peer-reviewed papers in academic journals before leaving the job

STATISTICAL SOFTWARE

SAS, Python (Pandas, Scikit Learn), SPSS, SQL, Excel, PowerPoint

DETAILED ANALYTICAL EXPERIENCES

Basic statistics/significance testing, factor analysis, ANOVA, OLS linear regression, logistic regression, Discriminant analysis, market segmentation (cluster analysis), Path analysis, repeated measures, GLM(Generalized Linear Modeling), MaxDiff Analysis, Perceptual Mapping, Van Westendorp Pricing Sensitivity, Choice-Based Conjoint modeling, Market Preference Simulation (VBA in Excel), CHAID, Decision Tree, PLS(Partial Least Square) Model, Proportional Hazard Model (survival analysis), Multinomial Logit Modeling, Poisson Regression, Neural Network, Time Series Forecast, Structural Equation Modeling, and Market Basket Analysis, various Machine Learning Models in Python.

EDUCATION

University of Louisville, Louisville, KY

Ph.D. in Public Policy, 2005

Main strength: Statistics, Research Methodology

MA in Sociology, 1999

Main strength: Statistics, Research Methodology

CERTIFICATION

DMA Certified Marketing Professional 201

RELOCATION/

SPONSORSHIP

Not willing to relocate. Naturalized US Citizen. No employment sponsorship needed.

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