Will Kurt
Seattle, WA | wckurt@gmail.com | github.com/willkurt
Summary
Data Science and AI engineering leader with 10+ years of experience spanning machine learning, data science, and software development. Specialized in LLM architecture, prompt engineering, and inference optimization with proven success in both startup and enterprise environments. Published author of two technical books and creator of the Count Bayesie blog (10k+ monthly readers). Combine deep technical expertise with strategic vision to deliver impactful Data Science and AI solutions that drive business growth and technological advancement.
Experience
Senior Principle Data Scientist
- Lead Engineer for Supply and Demand product pillar
- Develop and deploy key forecasting models: price decay, unconstrained demand, etc.
- Model inventory lifecycle observability to provide critical insights to the operations team
- Provide one-on-one mentorship to junior engineers
Founding Engineer + Advocate
- Established product groundwork directly tied to $12 million VC raise
- Co-designed and implemented novel LLM-inference algorithm resulting in 2-5x speedup
- Successfully beat GPT-4 on "Function calling" tasks with open weights model
- Collaborated on engineering and content work with HuggingFace and Deeplearning.ai
- Led Advocacy team activities driving core GitHub repo to over 10k stars
Staff AI Engineer
- Managed internal evaluation framework to measure text-to-SQL LLM performance
- Implemented prompt engineering techniques for improved SQL generation
- Developed table metadata Retrieval Augmented Generation (RAG) system
Senior Data Scientist — AI/ML Team
- Developed AI algorithm for automatic subject line testing using GPT-3 and HuggingFace; achieved performance on-par with standard A/B testing
- Designed and developed novel, user-level, interaction-based A/B testing framework providing users up to 5% conversion lift over traditional A/B tests
- Implemented probabilistic sales account scoring model with potential 20% conversion increase
Lead Data Scientist (Manager) — Pricing Team
- Directly managed activities of the Pricing & Recommendations data science team
- Developed optimal pricing strategies for fintech-related product lines
- Implemented dynamic pricing algorithms in TensorFlow
Data Science Technical Lead
- Developed statistical testing for large-scale product experiments (Hive and Python)
- Collaborated across departments to improve scalable, big data infrastructure for the DS team
- Implemented and deployed the "early orders" model to predict product performance
Senior Data Scientist
- Developed large-scale behavior models to predict firmographic information from IP traffic
- Engineered features and created models on multi-terabyte datasets using PySpark
- Debugged and tested production machine learning implementations
Head Data Scientist
- Led all data science, machine learning, and analytics-related projects
- Developed and deployed a highly scalable web application (Python/React/AWS Lambda/Redis)
Lead Data Scientist
- Directed and managed the activities of the data science team
- Implemented A/B testing tool in core product using JavaScript and Ruby
- Led implementation of customer-facing time series forecasting
- Developed Markov chain-based attribution models
Publications
A Damn Fine Stable Diffusion Book
Bayesian Statistics the Fun Way
Get Programming with Haskell
Education
MS in Computer Science
MS in Library and Information Science
BA in English with Honors
Technical Skills
Programming
- Python
- TypeScript
- R
- Haskell
- C++
AI & Machine Learning
- Large Language Models
- Prompt Engineering
- LLM Evaluations
- Diffusion Models
- JAX
- PyTorch
- TensorFlow
- A/B Testing
- Causal Inference
- Bayesian Statistics
Data Engineering & Infrastructure
- LanceDB
- Snowflake
- MongoDB
- Redis
- PySpark
- Airflow
- AWS