Resume - Dr. Alex Vance | Principal Data Scientist

Executive Summary

Principal Data Scientist with 9+ years of experience translating massive multi-terabyte datasets into over $18.4M in quantified business impact. Proven track record leading cross-functional analytics teams across Netflix, Uber, and high-growth FinTech. Expert in causal inference, probabilistic time series forecasting, scalable deep learning recommendation systems, and executive C-suite communication.

Work Experience

Principal Data Scientist · Netflix Analytics

2023 – Present · Los Gatos, CA

Architected the global Subscriber Lifetime Value (LTV) and multi-horizon churn forecasting engine on Snowflake, Spark, and XGBoost, achieving 0.892 AUC-ROC.
Saved $4.2M in annual recurring revenue by developing automated churn early-warning playbooks for 18.4M active accounts.
Led a team of 6 senior data scientists; pioneered causal synthetic control methods to measure content release incrementality across 40+ international regions.

Senior Machine Learning Scientist · Uber Marketplace

2020 – 2023 · San Francisco, CA

Engineered real-time dynamic supply-demand spatial pricing models processing 12,000 requests/sec with <15ms p99 latency in Go and PyTorch.
Increased marketplace driver utilization by 14.8% and reduced passenger ETAs by 1.6 minutes during severe peak surges.
Designed and analyzed 80+ large-scale cluster-randomized A/B experiments across North America and EMEA markets.

Senior Analytics & BI Engineer · Airbnb Growth

2017 – 2020 · San Francisco, CA

Built unified multi-touch attribution (MTA) and Bayesian media mix models (MMM) optimizing $24M in annual digital marketing spend.
Reduced customer acquisition cost (CAC) by 27% and increased Return on Ad Spend (ROAS) from 2.9x to 3.8x.
Built production dbt transformation pipelines serving executive reporting dashboards for 450+ internal stakeholders.

Education

Ph.D. / M.S. in Statistics & Data Science · Stanford University

2013 – 2017

Dissertation: Bayesian Nonparametric Causal Inference in High-Dimensional Spatial Networks (Advisor: Prof. Robert Tibshirani lab).

B.S. in Computer Science & Applied Mathematics · UC Berkeley

2009 – 2013

Summa Cum Laude, Tau Beta Pi Honor Society, GPA 3.96/4.0.

Technical Expertise

Languages: Python (NumPy, SciPy, Pandas, PyTorch), R, SQL, Scala, Bash

ML & Modeling: XGBoost, LightGBM, Scikit-Learn, TensorFlow, SHAP, CausalML, Prophet

Data Engineering: Snowflake, BigQuery, ClickHouse, Apache Spark, Kafka, dbt, Airflow

BI & Viz: Tableau, Power BI, Looker, Streamlit, Plotly, HTML5 Canvas D3

Cloud & DevOps: AWS (SageMaker, S3, EMR), GCP (Vertex AI), Docker, Kubernetes, Git

Specialties: Causal Inference, A/B Testing, Time Series, Fraud Detection, RecSys

Honors & Certifications

AWS Certified Machine Learning - Specialty · Databricks Certified Data Scientist Associate · Tableau Desktop Certified Professional · Google Professional Data Engineer · KDD Best Applied Data Science Paper Nominee (2024).