Business Intelligence Machine Learning

JINYANG ZHANG

732-***-**** • *******@*****.*** • Linkedin.com • Data Portfolio

EDUCATION

University of Massachusetts Amherst, Isenberg School of Management Master of Science in Business Analytics September 2024

• Relevant coursework: Data Management for Business Leaders; Business Intelligence & Analytics; Business Application Development; Project Management; Marketing Strategy; Leadership & Organizational Behavior; Financial Management

Bachelor of Science in Economics December 2023

• Relevant coursework: Industrial Organization; Game Theory; Econometrics; Money & Banking; Financial Analysis; Intermediate Macro & Microeconomic Theory; Financial Accounting; Decision Analysis; Intermediate Statistics for Business

UPenn Wharton

Certificate in Business Analytics Specialization February 2023 SKILLS & CERTIFICATIONS

DBMS, SQL, Tableau, Python, R and R Studio, VBA for Excel, MS Advanced Excel with Power BI, Apple Swift, SAP Business Objects Analysis, SAP Predictive Analytics, Supervised & Unsupervised Machine Learning, MS Project Publishing: Project Management Simulator, MS Word, PowerPoint & Access Python: Programming Fundamentals (Iteration, Conditioning, Functions), Libraries (NumPy, Pandas, Matplotlib, Seaborn, Statsmodels, scikit-learn), Jupyter / Colab Notebooks Analytics: Financial & Performance Analytics, Predictive & Statistical Modeling, Customer & Market Insights, HR & Talent Analytics, Operational & Risk Management, Technology & Data Management, Financial Forecasting Other: Storytelling & Visualization, Data Mining, Text Mining, Account Reciliation Languages: Native Chinese, Fluent English

Certifications: Business Analytics Specialization, UPenn Wharton; Google Data Analytics, Coursera PROJECTS EXPERIENCE

Python & Machine Learning: Exploratory Analysis of NBA Shooting Zones Spring 2024

• Scraped NBA team shooting zone data spanning eight seasons from NBA.com/stats, utilizing Pandas and BeautifulSoup to compile unified dataset; visualized playoff teams’ field goal attempts per game against offensive rating using matplotlib

• Analyzed shot selection trends in modern three-pointer-heavy NBA, identifying that teams can still achieve success with high volume of mid-range jump shots by examining team-wide shot profiles linked to highest offensive ratings Tableau: Business Intelligence & Analytics Fall 2023

• Prepared CSV files by renaming, deleting, calculating fields and re-formatting to Tableau native format

• Formulated six research questions about box office performance of movies in 2022 (topic of data set), and generated necessary calculated fields when needed to answer them

• Used visualization principles such as pre-attentive processing, data-ink ratio, and eloquence through simplicity to communicate findings in most concise and clear way possible

• Showed results in Tableau dashboard using scatterplots, pie charts, bullet graphs, and other chart types; presented findings as PowerPoint to peers

Excel: Data Management for Business Leaders Fall 2023

• Created interactive Excel dashboard to help users evaluate options for new place to live; dashboard based on five data sets using Power Pivot and Excel data model

• Dashboard includes macros to help users easily navigate information presented, as well as pivot tables, slicers, drop-down lists, and conditional formatting to convey key takeaways R & ggplot2: Data Analysis in Sports Fall 2023

• Analyzed correlation between swing launch angles and offensive performance in professional baseball using R Studio, visualizing results through ggplot2 and presenting findings in poster session

• Collected and processed data on exit velocity, launch angle, and other key statistics from public sources; performed regression analysis, identifying statistically significant relationship between higher launch angles and improved hitting performance

EMPLOYMENT EXPERIENCE

C.H. Educational & Financial Consulting Group Boston, MA Co-Founder Business Analyst & Data Consultant June 2020-December 2024

• Analyzed financial and operational data to optimize business performance, boosting client profitability by 15%.

• Built predictive models in Python and SQL, increasing customer retention

• Enhanced sales forecasting with Excel and Power BI, improving revenue accuracy

• Automated reporting with Tableau and Power BI, reducing manual workload

• Conducted market and risk analysis, driving data-informed investment decisions.

Contact this candidate