Maria Garcia

maria.garcia@email.com · (206) 555-0183 · Seattle, United States linkedin.com/in/mariagarcia

Senior Data Scientist

Data scientist with 5+ years of experience building ML models that drive business decisions at scale. Expertise in recommendation systems, NLP, and experimentation. Passionate about translating data into product impact.

▸ Experience

Senior Data Scientist @ Amazon

2020-06 – Present · Seattle

• Designed a real-time personalization system using collaborative filtering that increased product recommendation click-through rates by 28% across 50M+ users.
• Built an automated A/B testing platform serving 300+ concurrent experiments, reducing analysis time from days to minutes with sequential testing methods.
• Developed a churn prediction model using gradient boosting that achieved 94% precision, enabling proactive retention campaigns that reduced monthly churn by 22%.
• Presented ML roadmap and experiment results to VP-level stakeholders, directly influencing $200M+ in product investment decisions.

Data Scientist @ Spotify

2018-01 – 2020-05 · United States

• Built NLP models for sentiment analysis on customer reviews, processing 10M+ documents daily with 87% accuracy.
• Created a causal inference framework to measure marketing campaign effectiveness, optimizing $50M annual ad spend across 20+ channels.
• Developed feature engineering pipelines in Spark processing 5TB+ of daily event data for ML model training.

▸ Education

Ph.D., Computer Science (ML)

University of Texas at Austin · 2013-09 – 2017-06

B.S., Mathematics

University of California, San Diego · 2009-09 – 2013-06 · GPA: 3.9

▸ Skills

Machine Learning: Deep Learning · Recommendation Systems · NLP · Causal Inference · A/B Testing Engineering: Python · PyTorch · Spark · SQL · AWS SageMaker

▸ Certifications

AWS Certified Machine Learning Specialty (2023) TensorFlow Developer Certificate (2022)

Open Source

• Contributed feature engineering modules to scikit-learn that received 500+ GitHub stars

Speaking

• ML Conference 2024 - "Production ML at Scale" talk
• Data Science Summit 2023 - Workshop on causal inference

Publications

• Garcia, M. et al. "Efficient Collaborative Filtering at Scale." KDD 2023.