Tel:+1-310******* Email:firstname.lastname@example.org LinkedIn:www.linkedin.com/in/shu-jiang
Experienced business analyst, data analyst who aims at finding Business Intelligence Operation job, with sufficient project experience in machine learning, computer networking, analytical thinking and creative problem solving. Strong knowledge of solutions-oriented approach while driving business growth, and strategic alliances.
Business Analyst 5/2019 to Current
• Operated and analyzed the company’s business work, participated in major business decisions, organized the formulation of marketing development strategies.
• Collected market information, customer feedback, competitor strategy analysis.
• Led business process and workflow mapping/analysis using data capture and modeling technologies, methods and tools.
• Applied machine learning (Logistic Regression, decision tree), analyzed the important feature of business, user and technical requirements
• Grasped the needs of end users and partners, delivered various business strategies according to analyzed business insight, wrote and updated website operation analysis reports in time, and put forward reasonable suggestions. Data analyst 11/2018 to 5/2019
Silicon Valley Center
• Applied web scraping methods to extract data from open sources and various customer account websites, processed and cleaned data integrity for analytics.
• Conducted statistics exploratory analysis in SAS and Python, developed and optimized dashboards with Tableau to maintain adequate supplies to reduce risk, drawn actionable insights and managed client expectations, which significantly increased due to implementation of revised, streamlined operations.
• Developed marketing strategy including the machine learning (logistics model) on different campaigns or channel levels to capture profitable markets, potential customer and fostered brand identity and growth.
• Slashed payroll/benefits administration costs 30% by negotiating pricing and fees, while ensuring the continuation and enhancements of services. Analyzed and checked the collecting membership statements and thereby increased 30% benefits Successfully. Selected Projects
San Francisco Crime Analysis in Apache Spark May 2020
• Performed spatial and time series analysis for a 15 year dataset of reported incidents from SFPD
• Build data processing pipeline based on Spark RDD, Dataframe and Spark SQL for big data OLAP
• Trained and fine-tuned an ARIMA model to forecast the number of thefr incidents per month
• Explored and visualized the variation of the spatial distribution of incidents over time Banking Customer Churn Prediction and Analysis Feb 2020
• Developed machine learning models for the bank to predict customer churn and analyze the key factors based on labeled data in Python(Pandas, Sklearn)
• Preprocessed data set by data cleaning, categorical feature transformation, and regularization, standardization, etc.
• Trained supervised machine learning models including Logistic Regression, Random Forest and K-Nearest Neighbors, and applied regularization with optimal parameters to avoid overfitting.
• Evaluated model performance of classification (accuracy or F1 score XX) via k-fold cross-validation technique and analyzed feature importance to identify top factors that influence the result Customer Spending Behavior Analysis on Client Invoice Data Sept 2019
• Cleaned a raw dataset (data cleaning, data mining), reformatted variable values into numerical data, and imported dataset into Python.
• Performed the user consumption period analysis and layered user value. Further refined operations, use models to predict the effective life cycle of users. Built predictive models including Decision Trees, Regression, and Neural Network; did A B testing using SAS and Python.
• Provided detailed guidance based on their characteristics to promote consumption growth. Education
Bachelor of Science: Applied Mathematics, Statistics Aug 2018 San Jose State University (Silicon Valley)
• Related course work: Mathematical Statistics, Theory of Probability, Business Management, Finance Modeling, Finance Analysis, Investment Analysis, Linear Algebra, Numerical Analysis and Scientific Computing, Programming in R, Programming in Python. Skills
• Programming: Python (pandas, numpy, sklearn), SQL, R, SPSS, Matlab
• Machine Learning: Logistic Regression, Regularization, Clustering, K Nearest Neighbors, K-means, Principal Component Analysis(PCA), Decision Trees.
• Excellent analytical, Problem Solving & Critical, Strong Verbal & Written communication skills
• Software/Technology: Strong skills in Micro Office (Excel, Word), Tableau.
• Statistics: Hypothesis Testing, Text Mining, Data Mining, Data Cleaning