Sitong Chen Email & Phone Number

New York, Ny, Us

New York, New York, United States

New York, United States

New York, United States

• Led a comprehensive MaxDiff survey analysis, employing Mlogit and Hierarchical Bayesian methods to accurately decipher customer preferences, setting the groundwork for enhanced retention strategies.• Executed advanced cluster analysis utilizing Umap and Consensus Cluster techniques to effectively categorize customers into five distinct groups, facilitating targeted and efficient retention initiatives.• Developed a sophisticated Customer Classification System using a variety of Machine Learning algorithms, leveraging multifaceted data variables to predict customer behavior with a precision rate of up to 32%.• Analyzed customer preference patterns and profiles within each group to design and implement tailored retention rewards, significantly contributing to the strategic goal of improving customer loyalty and satisfaction.

West Lafayette, Indiana, United States

•Identifying business insights and key factors affecting the efficiency of the Dow Chemical supply chain process in view of 3+ years of data•Developing machine learning models to capture the variability of leading time and effects of shipping mode as well as material types•Proposing a data-driven prescriptive model to optimize material operation progress and supply chain manufacturing efficiency•Awarded 2nd place in the Purdue University OUR Conference 2023 Research Talk

West Lafayette, Indiana, United States

•Descriptive Analytics: conducted post-mortem analysis by mining historical data from coating suppliers in the synthetic fibers industry and identified product stability and stain resistance as response variables to figure out the best manufacturing process parameters•Predictive Analytics: developed a regression model by using ROI package from R to identify “optimal” decision recommendations•Prescriptive Analytics: built three constraints combination optimization models including stability & stain resistance constraints, max-min constraints as well as convex hull constraints to improve model accuracy and achieved maximum carpet stain resistance ability•Awarded 1st Place in Posters at the Purdue University 2022 Fall Undergraduate Research Expo

West Lafayette, Indiana, United States

•Data Wrangling: explored, reshaped and filtered data in the Multi-Radar/Multi-Sensor and Global Forecast System with Python•Image Segmentation: build semantic segmentation models with one-dimensional pixels, 2+-dimensional pixels and incorporate dependency across frames by using publicly available radar data, evaluated models with Mean IoU and Pixel Accuracy metrics•Predictive Analytics: performed predictions of severe weather risks and identified model accuracy with Global Forecast System data; oriented the modeling framework to predict variables of more interest involving resultant property claim frequency and severity

•Scraped and wrangled customer mobility patterns and foot traffic data from 2019 to 2021on 5 airports through Python and R •Applied spatial analytics by building Huff model with ArcGIS Pro to estimate visiting probability in 3-level distance cut-off•Compared model outputs with real mobility yearly data and evaluated model effectiveness by generating visualization maps •Received 2nd place in the Purdue University OUR Conference Research Talk and 2nd place in the 2022 Annual Indiana GIC Conference Student Project Contest•Published the research result in the Journal of Purdue Undergraduate Research 2022

Remote

•Set up campaign missions for data collection and explored market demand; managed user inputs and translated into client needs•Monitored campaign progress by keeping track of conversion rate, bounce rate, web traffic as well as checking engagement level •Built interactive real-time dashboards to display visualized charts using SQL; generated analysis reports to provide business insights

United States

• Promoted the telecom business by maintaining existing channel partners and expanded 15+ additional partners• Analyzed data and summarized overall revenue to provide data support for future operation expansion• Designed 3+ proposals for cooperation activities between the company and customers, worked with the merchants to modify the details and requirements of the plan

Seattle, Washington, United States

•Facilitated data gathering to drive business by formulating strategies, developing execution plans, and measuring performances •Participated in financial performance evaluation, monthly and quarterly forecasting, scenario modeling, and sensitivity analysis •Reviewed reconciliation, made asset management recommendations on equities and fixed income; delivered supporting details

Master'S Degree, Industrial Engineering And Operations Research

Bachelor'S Degree, Supply Chian Info/Analytic & Industrial Management, 3.9

Activities and Societies: Minor: Statistics; Certification: Applications in Data Science, Lean Green Belt Certification; Dean’s List.