
Richard
MBA candidate
Expertise
Business, Economics, Sports Data & Analytics, Psychology
Polygence mentors are selected based on their exceptional academic background, teaching experience, and unique ability to inspire the next generation of innovative thinkers and industry leaders.
Business, Economics, Sports Data & Analytics, Psychology
Machine Learning, Security, Privacy, Data Science, Statistics, Computer Science
Business Analyst, Data Analyst, Business Intelligence, Process flow
Business, IT Audit, Consulting, accounting
NCAA, NFL, NASCAR, and NBA industry experience; consulting across sports business and analytics; DraftKings analytics; published sports economics research; SQL, Python, and R programming; Tableau data visualization; Microsoft Office Suite; strategic insights in sponsorship, ticketing, and fan engagement.
marketing, consumer behavior, entrepreneurship, journalism, market research, journalism, culture, music, urban studies, civic engagement, community
Currently an adjunct professor at La Salle University teaching Sports Finance to undergraduates & Managerial Accounting to MBA students, been in the sports industry now for 5 years revolving around accounting, finance, sports business analytics etc.
Sports Analytics
Sport Analytics and Data Science
Sport Analytics, Data Science, Programming, Econometrics
Business, technology, economics, sports analytics, Chinese language/culture/politics
Economics, Sports, Business, Math, Stats, Data Science
Data science, Sports analytics, Bayesian statistics, Machine learning
Data Science, Data Analytics, Machine Learning, Sports Analytics, Natural Language Processing, Data Visualization, Computer Science, Biotechnology
Marketing, economics, business analytics, sports analytics, consulting, pricing, sports market analysis
Physics, Optics, Quantum Mechanics, Math, Sports Analytics, Scientific Writing, Science Communication
computer vision, AI for sports, data science, GPU programming
business strategy, analytics, economics
Data Science
Statistical Analysis, including regression analysis, machine learning, and use of R and Python. Statistical analysis in topics such as politics, physics, chemistry, astronomy, public health, and medicine. Biostatistical Analysis, including longitudinal studies and survival analysis