# Adrian Cole Headline: Data Scientist Specializing in Machine Learning and Predictive Analytics - Email: adrian.cole@example.com - Phone: (415) 555-0142 - URL: https://adriancole.dev Location: 456 Mission Street, San Francisco, California, United States, 94110 Profiles: - GitHub: [@adriancole](https://github.com/adriancole) - LinkedIn: [@adriancole-data](https://www.linkedin.com/in/adriancole-data) ## Basics Data scientist with 6+ years of experience building machine learning systems that turn messy data into measurable business impact. Strong background in statistics, causal inference, and natural language processing, with deep expertise across the full model lifecycle—from problem framing and data pipelines to deployment and monitoring. Passionate about creating interpretable, reliable models and translating data insights into clear recommendations for product and leadership teams. ## Education ### University of California, Berkeley Master, Information and Data Science, Score: 3.9, Aug 2016–May 2018 URL: https://www.ischool.berkeley.edu/ Courses: Applied Machine Learning, Statistics for Data Science, Natural Language Processing, Big Data Systems, Experimentation and Causal Inference, Data Visualization Summary: - Concentrated on machine learning, causal inference, and large-scale data systems - Capstone project: built a real-time churn prediction pipeline for a telecommunications partner - Graduate research assistant supporting a study on algorithmic fairness in lending decisions ### University of Washington Bachelor, Statistics, Score: 3.8, Sep 2012–Jun 2016 URL: https://www.stat.washington.edu/ Courses: Statistical Inference, Regression Models, Probability Theory, Computational Statistics, Data Mining Summary: - Built strong foundations in statistical theory and computational methods - Undergraduate research assistant in the Statistical Learning Lab ## Work ### Senior Data Scientist Lumina Analytics, Mar 2021–Present URL: https://www.lumina-analytics.com/ Keywords: Python, MLflow, Feature Store, Causal Inference, Mentorship Summary: - Lead development of predictive models for customer lifetime value across a portfolio of SaaS clients, improving average revenue forecast accuracy by 18% - Architect feature store and model monitoring pipelines using Python and MLflow, reducing model retraining time from days to hours - Partner with product and engineering teams to design A/B tests and causal inference studies for new feature adoption initiatives - Mentor a team of four data scientists and establish best practices for code review, reproducibility, and documentation ### Data Scientist HealthInsight, Jul 2018–Feb 2021 URL: https://www.healthinsight.com/ Keywords: Healthcare, NLP, Tableau, Electronic Health Records Summary: - Built risk stratification models using electronic health records and claims data, enabling early intervention for high-risk patients - Designed and implemented an NLP pipeline to extract clinical concepts from unstructured notes, achieving 87% F1 score - Created interactive Tableau dashboards used by clinical leadership to track quality metrics and reduce hospital readmission rates by 12% ## Languages - English: Native or Bilingual Proficiency, Keywords: IELTS 8.5 - Spanish: Full Professional Proficiency, Keywords: DELE C1 ## Skills - Machine Learning: Expert, Keywords: Python, scikit-learn, XGBoost, TensorFlow, PyTorch - Statistical Modeling: Advanced, Keywords: R, Bayesian Methods, Time Series, Survival Analysis, Experiment Design - Data Engineering: Advanced, Keywords: SQL, Spark, dbt, Airflow, AWS, Snowflake - Natural Language Processing: Advanced, Keywords: Hugging Face, spaCy, Transformers, NER, Topic Modeling - Data Visualization: Intermediate, Keywords: Tableau, matplotlib, Plotly, ggplot2 ## Awards ### Outstanding Contribution in Data Science Lumina Analytics, Dec 2023 Summary: Recognized for leading the development of a company-wide model monitoring platform that reduced unplanned model retraining incidents by 40%. ## Certificates ### AWS Certified Machine Learning - Specialty Amazon Web Services, Nov 2021 URL: https://aws.amazon.com/certification/certified-machine-learning-specialty/ ### TensorFlow Developer Certificate Google, Apr 2020 URL: https://www.tensorflow.org/certificate ## Publications ### A Scalable Framework for Real-Time Customer Churn Prediction Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Aug 2022 URL: https://doi.org/10.1145/3523227.3547400 Summary: - Presented a production-ready churn prediction framework combining gradient-boosted trees with online feature stores - Demonstrated a 23% relative improvement in AUC versus batch baselines across three industrial datasets ## Projects ### DocQuery An NLP-powered search and question-answering tool for unstructured clinical documents., Jan 2023–Jun 2023 URL: https://github.com/adriancole/docquery Keywords: NLP, Transformers, Q&A, Docker, FastAPI Summary: - Developed a retrieval-augmented system using sentence embeddings and a fine-tuned transformer model to answer clinician questions from EHR notes - Deployed as a REST API with Docker, reducing average answer lookup time from 20 minutes to under 5 seconds ### AdScore Click-through rate prediction model for online advertising campaigns., Aug 2020–Dec 2020 URL: https://github.com/adriancole/adscore Keywords: CTR, PySpark, Feature Engineering, ONNX Summary: - Engineered features from impression logs and built a distributed training pipeline in PySpark - Achieved a 15% lift in offline AUC and enabled real-time bidding through model export to ONNX ## Interests - Open Source: Contributing to scikit-learn, Jupyter, Streamlit - Hiking: Yosemite, Pacific Crest Trail - Chess: Tournament Play, Puzzle Solving ## Volunteer ### Bay Area Data Corps Data Science Volunteer, Mar 2022–Dec 2023 URL: https://www.bayareadatacorps.org/ Summary: - Partnered with local nonprofits to analyze service utilization data and guide resource allocation decisions - Built reusable notebook templates to standardize weekly reporting and make findings accessible to nontechnical staff