Emily Qiu

About Emily Qiu

Open to full-time roles in Data Science or Machine Learning Engineering in the San Francisco Bay Area | F-1 OPT & H-1B sponsorship welcome | Technical, client-facing, and cross-functional opportunities encouraged A data professional with a passion for solving real-world problems through the lens of machine learning and statistical modeling. Strong mathematical training (First-Class Honours in Applied Mathematics from the University of Edinburgh) and advanced analytics education (UC Berkeley, GPA 3.96) form the backbone of a technical skillset built on Python, SQL, R, LightGBM, Streamlit, SHAP, BERT, and AWS. Projects span recommender systems, satellite super-resolution, poker strategy simulation, and airline waste forecasting — each designed for performance, clarity, and impact. Highlights include a three-stage hybrid recommender system deployed via Streamlit with 31% improvement in precision@5, and a SAR image enhancement model supporting post-earthquake mapping efforts in Turkey. Known for strong communication across disciplines — from collaborating with engineers and planners to presenting insights using SHAP, A/B testing, and interpretable dashboards. Thrives in high-performance teams and embraces independent deep work. Equally comfortable building ML pipelines and translating outcomes to non-technical audiences. With experience in international schools in Shenzhen, undergrad studies in Edinburgh, and graduate training in Berkeley, brings a deep appreciation for cultural diversity and learning environments. Bilingual in Mandarin and English, conversational in Spanish and Cantonese, and currently learning Italian. Drawn to the Bay Area for its innovation, clean energy, and culture of growth. Every conversation offers an opportunity to learn, expand, and contribute meaningfully to mission-driven teams across industries. Outside of work, passion flows into jazz, opera, classical concerts, hiking, snowboarding, fashion, and learning new sports like tennis. Enjoys discussing the intersection of business, technology, and society — from company case studies to political dramas — always curious, always learning. Skills Snapshot: • Languages & Tools: Python, SQL, R, MATLAB, Tableau, Power BI, LaTeX • Libraries: Scikit-Learn, LightGBM, PyTorch, Huggingface, FAISS, SHAP, Pandas, NumPy • Systems: AWS, Azure, Hadoop, Spark, PostgreSQL, Git, Docker • Techniques: Feature Engineering, Model Evaluation, Cross-Validation, A/B Testing, SHAP, PCA, Time Series, NLP Portfolio: https://emilyqiu720.github.io Email: e••••••••@outlook.com

Experience

1. Data Scientist

   Zipline

   Jun 2025 — Present · San Francisco, CA, US

   Currently supporting Zipline’s engineering and data science teams to model drone energy consumption for large-scale autonomous medical deliveries across Africa. Zipline operates the world’s largest drone delivery network, delivering critical supplies like vaccines, blood, and medications to remote and underserved areas with unmatched speed and reliability.The focus of this internship is to build a predictive model for energy consumed using high-frequency telemetry and environmental features, such as route distance, GPS altitude, wind conditions, and payload characteristics. Responsible for designing a feature extraction pipeline at 10-second flight intervals and exploring regression frameworks to capture how flight conditions influence battery usage.Efforts are aimed at improving Zipline’s fleet-level energy forecasting, enabling smarter battery allocation and reducing mission failure due to power constraints. Final outputs are intended to support future automation and routing decisions that improve delivery efficiency in rural and low-infrastructure regions.This internship is ongoing and expected to conclude on August 15, 2025.

Education

• University of California, Berkeley

  Master of Analytics, Analytics

• The University of Edinburgh

  Bachelor of Science (Hons), Applied Mathematics

  2020 — 2024

• Chapel Field Christian High School

  High School Diploma