Open to opportunities

William Morse

@williammorse

Message

Senior data scientist specializing in fraud detection, ML pipelines, and scalable data systems.

United States

Message

What I'm looking for

I seek roles where I can lead fraud detection and ML platform work, collaborate cross-functionally, mentor teams, and deliver measurable reductions in fraud and operational cost.

I am a senior data scientist with over 10 years of quantitative experience building fraud detection and remediation systems that balance fraud loss, cost, and customer experience.

I design and ship production ML pipelines and feature stores, applying Python, Spark, BigQuery, and modern ML frameworks to improve accuracy, scalability, and explainability.

At scale, I have reduced fraudulent transactions, improved detection latency, and saved millions annually while implementing monitoring, governance, and reproducible ETL/ELT.

I collaborate cross-functionally with product, finance, security, and operations, mentor junior engineers, and use advanced LLMs and explainability tools to detect emergent misuse and operationalize models.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Scientist

Current

Uber Eats

Feb 2021 - Present (5 years 1 month)

Led design and implementation of enterprise fraud detection and remediation pipelines, reducing fraudulent transactions by 31% and saving $3.2M annually while improving detection latency by 85%.

Python Spark XGBoost Kafka Apache Beam BigQuery Airflow MLFlow

Data Scientist

Oct 2017 - Jan 2021 (3 years 3 months)

Led enterprise fraud scoring models for global payments, decreasing false negatives by 27% and preventing an estimated $1.8M in losses while scaling batch and streaming pipelines to 200M events daily.

Python LightGBM Spark Airflow Kafka BigQuery Feast

Data Scientist

Symufolk

Jul 2016 - Sep 2017 (1 year 2 months)

Built abuse detection prototypes and ETL pipelines, reducing chargebacks by 21% in pilots and lowering manual review volume by 35% through rule-based remediation.

Python scikit learn XGBoost Airflow Spark Postgres Docker Kubernetes

Data Scientist

Insilicom LLC

Jun 2015 - Jun 2016 (1 year)

Designed fraud scoring experiments and ETL pipelines, improving detection lift by 18% and reducing data latency from hours to minutes to enable faster model retraining.

R Python SQL scikit learn Airflow Tableau MLFlow

Education

Degrees, certifications, and relevant coursework

University of Florida

Master of Science, Computer Science

2014 - 2015

Completed a Master's degree in Computer Science with coursework and projects focused on applied machine learning and large-scale data processing.

University of Florida

Bachelor of Science, Computer Science

2010 - 2014

Completed a Bachelor's degree in Computer Science covering programming, algorithms, and data systems used to support subsequent work in data science and machine learning.