Tim Hopper

💻 Experienced machine learning engineer and Python developer

Experience

Varo Bank
Sr. Staff Software Engineer, Machine Learning, March 2024 - present
Staff Software Engineer, Machine Learning, December 2021 - March 2024

• Develop machine learning platform for fraud detection, risk mitigation, lending, and marketing
• Lead development of batch feature store using Tecton, enabling democratized feature creation and discovery
• Guide team in implementing engineering best practices

DTN
Data Science Architect, August 2020 – December 2021

• Built and maintained data science infrastructure with AWS and CloudFormation
• Enabled machine learning product development by building tools and platforms for data scientists
• Trained and mentored data scientists in Python tooling and software engineering practice
• Strategized and led the development of AWS infrastructure for big data usability and accessibility

Blackberry | Cylance
Senior Data Scientist, Nov 2017 – May 2020

• Led development of feature store using serverless AWS infrastructure
• Developed and maintained Python packages for data ingestion, cleaning, and standardization
• Guided data science team in best practices for Python development and software testing
• Researched machine learning techniques for dynamic detection of malware

Distil Networks
Data Scientist, Oct 2015 – Nov 2017

• Led research for validation of JavaScript-based client fingerprinting technique
• Constructed hierarchical Bayesian models for analysis of internet user behavior
• Lead development of real-time identification platform for malicious web bots on Apache Storm
• Introduced team to best practices in Python development and data analysis

Qadium
Data Scientist, Feb 2015 – Oct 2015

• Built open-source tools in C++ and Python for topic modeling and inference on nonparametric Bayesian models
• Wrote instructional material for inference on nonparametric Bayesian models in with IPython notebooks
• Maintained continuous integration with Travis-CI and automated deployment to Anaconda.org

Parse.ly
Software Engineer, Jan 2014 – Feb 2015

• Developed algorithms in Python for aggregation of large-scale, streaming, time-series data
• Built and maintained lambda architecture on AWS using Storm, Elasticsearch, Redis, and Cassandra
• Contributed to streamparse, an open-source library for real-time stream processing in Python

RTI International
Data Scientist, Oct 2012 – Jan 2014

• Provided analytics and computational support for one of the nation’s leading nonprofit research institutions
• Contributed to projects on social media analysis for public health, environmental GIS modeling, nonlinear mixed effect modeling, and text-mining-based crime forecasting

Education

2010-2012

Master of Operations Research; North Carolina State University, Raleigh, NC

Research area: Reinforcement learning methods for healthcare operations

Instructor: Calculus 2

2009-2010

PhD Student in Mathematics; University of Virginia, Charlottesville, VA

No degree received

Instructor: Calculus 1 and Calculus 2

2004-2008

BS, Mathematics; Grove City College, Grove City, PA

Minor in Applied Physics; Minor in Computer Science; Summa Cum Laude

Technical Experience

Technical Tools

I have an experience with a breadth of tools for machine learning, software development, and backend engineering.

• Programming Languages (high proficiency): Python
• Programming Languages (some proficiency): C++, Go, C#, Mathematica, R, SQL, Java, Javascript
• Machine Learning Tools: Scikit-Learn, PyTorch, MLFlow
• Cloud Services: Amazon Web Services (Batch, Lambda, ECS, S3, SQS, Glue)
• Infrastructure and Configuration Tools: Terraform, Cloud Formation, Ansible, Saltstack

Open source contributions

Contributor to a variety of Python libraries, including

cpython · datamicroscopes · Streamparse · Conda · lda · Pandas

Personal Projects

• pydevtools.com: Ebook on Python developer tooling
• pythonplot.com: A Rosetta Stone of Python plotting libraries for exploratory data analysis
• Notes on Dirichlet Processes: Notes on Dirichlet processes for nonparametric Bayesian methods
• Into the Hopper: Podcast about machine learning and software engineering

tdhopper.com • resume@tdhopper.com • (919) 473-3145
Raleigh, NC USA