# Siyuan Zhu

> Data Scientist & Data Engineer| Experienced in Python, SQL, AWS, and Machine Learning | Columbia MS Applied Analytics

Location: Brooklyn, New York, United States
Profile: https://flows.cv/siyuanzhu

I'm a Master’s student in Applied Analytics at Columbia University, actively seeking full-time opportunities as a Data Scientist, Data Analyst, or Data Engineer starting in 2025.

With hands-on experience at Publicis Groupe, Alibaba, and a fintech startup, I’ve built end-to-end solutions using Python, SQL, AWS, PyTorch, Spark, and LLMs (GPT, LLaMA2, BERT)—ranging from NLP-driven medical diagnosis engines to cloud-based recommendation systems and financial analytics platforms.

Technical Highlights:

✅ Languages & Tools: Python (pandas, scikit-learn, PyTorch), SQL, R, Java, MongoDB, PostgreSQL

✅ ML & NLP: XGBoost, SVD, LSTM, BERT/ClinicalBERT, sentiment analysis, recommendation systems

✅ Cloud & Big Data: AWS (Lambda, EC2, S3), Oracle Cloud, Spark, Kafka, Flink, DBT

✅ Visualization: Tableau, Power BI, matplotlib, seaborn, Streamlit

✅ Data Engineering: ETL pipelines, data warehousing, cross-platform integration

I enjoy building scalable, data-driven systems that solve real-world problems and deliver measurable business impact. Native in Mandarin, I’m also passionate about hiking, cooking, and exploring innovations in AI and analytics.

📬 Let’s connect on LinkedIn or reach out directly at zhusiyuan0101@gmail.com.

## Work Experience
### Software Engineer @ General Motors
Jan 2025 – Present | Austin, Texas, United States

### Data Engineer @ Cmind Inc
Jan 2024 – Present | Boston, MA
• Designed and automated ETL/ELT data pipelines (Python, SQL) to ingest and transform 20k+ financial data sources from REST
APIs (e.g., FRED, Morningstar) into Oracle/PostgreSQL Autonomous Datawarehouse, achieving 99.9% reliability.
• Migrated MongoDB to a centralized data warehouse on Oracle Cloud and built cross-database synchronization for seamless data
integration, implemented data quality checks, scheduled daily updates, incident alerts (Slack, E-mail), and failure retry logic,
reducing product error rate by 90%.
• Engineered CSORE, a profitability composite indicator synthesizing peer group metrics and financial indicators reflecting company
profitability and quarterly performance to improve EPS (Earnings Per Share) prediction accuracy.
• Applied NLP (prompt engineering, few-shot learning with GPT-4o, FinBERT) to extract evasiveness/bullishness/sentiment from
earnings call transcripts, enhanced EPS predictive modeling and integrated results into warehouse tables for downstream BI.

### Data Scientist Intern @ Publicis Groupe
Jan 2023 – Jan 2023 | Shanghai, China
• Analyzed advertising strategies and monitored competitive placements, helping secure key client order renewals and win new pitches.
• Preprocessed data (Pandas) and applied regression models (linear regression, decision tree, XGBoost) to remove outliers, enhancing
data quality and reliability in strategic marketing decisions.
• Evaluated various Time Series Models (ARIMA, LSTM.) to predict traffic trends and choose promising video types for traffic allocation.
• Managed data (SQL) and built dashboards (Tableau) delivering market trend insights and performance benchmarks for 10+ clients.

### Teaching Assistant of CSE 3241: Introduction to database @ The Ohio State University College of Engineering
Jan 2022 – Jan 2022 | Columbus, Ohio, United States
•	Collected feedback from students, corrected 200+ weekly SQL assignments, rendered weekly reports to the professor
•	Held an office hour twice a week to assist students in learning algorithms and concepts of database systems and to answer students’ questions in SQL and database design projects

### Data Analyst Intern @ Alibaba Group
Jan 2022 – Jan 2022
• Developed an RFM model in R to segment 23k+ customers into 8 categories, enabling targeted marketing strategies.
• Analyzed 7M shopping records from 44k users on Taobao to identify key behaviors driving customer retention.
• Presented retention insights and actionable recommendations to high-level stakeholders, improving decision-making.


## Education
### Master of Science - MS in Applied Analytics
Columbia University
Jan 2023 – Jan 2024

### Undergraduate in Data Analytics
The Ohio State University
Jan 2018 – Jan 2022


## Contact & Social
- LinkedIn: https://linkedin.com/in/siyuan-zhu

---
Source: https://flows.cv/siyuanzhu
JSON Resume: https://flows.cv/siyuanzhu/resume.json
Last updated: 2026-04-01