Machine Learning Data Science

QIANQIAN ZHANG

San Jose, CA *****.******@************.*** 669-***-**** www.linkedin.com/in/qianqian-zhang-050123140 Education

Northeastern University (NEU) San Jose, CA

M.S. in Data Science Sep 2022 - Apr 2024

Northern Vermont University Lyndonville, VT

B.S. in Accounting and Business Administration Aug 2014 - May 2018 Technical Skills

Programming Languages: Python (Jupyter, PyCharm, VS), SQL (PostgreSQL, MySQL), R Methodologies: Machine Learning, Deep Learning, Natural Language Processing; Statistical Inference, A/B Testing, Hypothesis testing, Probability, Simulations, Confidence Intervals, Correlation, Regression, Time Series, Optimization Software: Excel(VLOOKUP, MACRO, VBA, PIVOT), Word, PowerPoint, PowerBI, Tableau, Google Analytics; GitHub Data Engineering: ETL, Data Extraction, Manipulation and Database Management, AWS, Data Pipeline, Hadoop, Hive, Spark Certificate: Tableau Desktop Specialist Certification (Passed) Work Experience

SiriusMindShare Lab San Jose, CA

Data Scientist Intern Jan 2024 - Sep 2024

● Developed a marketing email generator using NLP/LLM models to improve personalized targeting within email campaigns based on customer demographics, leading to a 15% increase in user engagement

● Iterated algorithms to reduce connection errors by 75% and boosting system response times by 50%

● Utilized automated prompt engineering techniques to optimize email generation across diverse industries such as retail, restaurants, and law firms to increase user satisfaction and flexibility in email customization

● Conducted A/B testing on industry-specific outcomes to improve content variation and observed an increase in CTR and conversions Trip.com Group Shanghai, China

Data Analyst Apr 2022 - Aug 2022

● Conducted A/B testing on the OTA platform to assess user behavior, resulting in a 15% increase in conversions among customer subgroups

● Developed a regression tree model to forecast global airfare pricing, incorporating features such as trip duration, seat layout, and fuel costs to achieve a 70% accuracy rate in itinerary pricing

● Designed interactive Tableau dashboards to provide stakeholders with real-time insights into funnel metrics of user journey milestones from signup to conversion and drop-off points

● Collaborated with airline representatives on travel destinations, resolving disputes, flight delays, and refunds to reduce company expenditure by an average of 25% per trip

China Mobile Guizhou, China

Research Analyst May 2020 - Mar 2022

● Designed and executed an audit strategy using SQL by analyzing database entity relationships and writing queries involving selections, joins, and grouping for comprehensive data extraction and analysis

● Led a team to establish data-driven strategies for incremental revenue growth which achieved a 40% profit margin

● Conducted a time series analysis for Network Failure Prediction, resulting in an 80% reduction in potential risk exposure Passumpsic Bank Lyndonville, VT

Marketing Analyst Intern Sept 2019 - Dec 2019

● Launched social media campaigns on platforms such as Snapchat, integrating automated content scheduling workflows resulting in a 50% increase in client engagement

● Implemented a cost-effective market campaign that boosted client relations by 72% within the first year

● Deployed automated interactive data visualization dashboard through PowerBI to track the key success metrics such as customer satisfaction ratings, conversion rate, and ROI, enabling real-time monitoring of marketing promotion strategy effectiveness Project Experience

Loan Eligibility Prediction Using Machine Learning Algorithms Sep 2024 - Oct 2024

● Analyzed and preprocessed data for downstream Machine Learning algorithms, such as over-sampling, scaling numerical variables, and missing value imputation

● Created Machine Learning classification models with various algorithms such as Logistic Regression, K Nearest Neighbor, Decision Tree, and Random Forest to predict loan eligibility

Bikes & Cycling Accessories Organization's Transactions Data Based Cohort Analysis Jul 2024 - Aug 2024

● Conducted Recency-Frequency-Monetization (RFM) analysis to understand the purchasing behavior of cohorts, uncovered insights into seasonality, promotional effectiveness, and cross-selling opportunities

● Developed cohort analysis of bicycle customers, creating heatmaps to identify seasonality patterns in customer retention rates using Python;

● Developed an ETL process using SQL and created a Power BI dashboard for revenue analysis across metrics to create pricing strategies Mobile Games A/B Testing with Cookie Cats for Player Retention May 2024 - Jun 2024

● Conducted data preprocessing, exploratory data analysis, and visualization to extract key insights for player behavior

● Calculated and compared 1-day retention and 7-day retention for control and treatment groups for significant differences

● Validated the certainty of retention rate differences via bootstrapping to quantify model robustness

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