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Tim Hopper
💻 I’m an experienced machine learning engineer and Python developer specializing in machine learning platforms, feature stores, and developer tooling. I aim to build tools that enable fast iteration on machine learning products that will drive business value and make customers happy.
Experience
Spotify
Machine Learning Infrastructure Engineer, October 2024 – present
Varo Bank
Sr. Staff Software Engineer, Machine Learning, March 2024 - October 2024
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
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
Education
- 2010-2012
Master of Operations Research; North Carolina State University, Raleigh, NC
Research area: Reinforcement learning methods for healthcare operations
Instructor: Calculus 2
- 2004-2008
BS, Mathematics; Grove City College, Grove City, PA
Minor in Applied Physics; Minor in Computer Science; Summa Cum Laude
Personal Projects
tdhopper.com • resume@tdhopper.com • (919) 473-3145
Raleigh, NC USA