- Senior Data ScientistMobilepaks2014 - PRESENT
- Conceived, prototypes, and product-ized data science initiatives. Responsible for researching models and writing the valuable ones into the app.
- Created a relevance score model applied to content based on how users consume and react to content. This ended up being a mathematic equivalent to a neural network, though training was primarily done by interviewing domain experts due to little available data.
- Created a model that generates tags attached to content based on who consumes what content in which context. (e.g., if lots of sales people consume a document and nobody else touches it, the content is probably for sales people).
- Documented and identified holes in current client-facing reporting infrastructure. Built new reports into the app as appropriate. My contribution mostly focused on the back-end, but occasionally required front-end work too.
- Upgraded the current search engine to include spellcheck, faceting on our current tag infrastructure, and autocomplete.
- Data ScientistSimor, via Grimm Science2014 - 2014
Technologies: Python, MS SQL Server, Recommendation algorithm
- Surveyed long-term applications of data science in the client's app.
- Reported potential short term new features that would leverage data science.
- Prototyped a recommendation engine designed to connect two similar people.
- Prototyped a complimentary recommendation engine to suggest potential teacher/student connections.
- Wrote a product version of the similar-people recommender.
- Data ScientistCloudability, via Grimm Science2014 - 2014
Technologies: Python, R, Holt Winters
- Surveyed time series prediction methods.
- Conducted a case study on time series prediction applied to server usage in R.
- Wrote product-quality implementation of the chosen time series model (holt winters) from scratch in Python.
- Calibrated forecasting intervals (expected accuracy on predictions) in terms of performance, and trained and tested sets of data.
- Documented model implementation and testing procedures to enable the client's engineering team to build the model into their dashboard.
- Senior Data ScientistSovolve, via Grimm Science2014 - 2014
Technologies: Linux, Python, PostgreSQL, Neo4j, Mixpanel
- Modeled user activity and interactions to optimize the user experience by filtering content to what is likely to be the most interesting and useful.
- Helped build out back-end data infrastructure to improve app performance and prepare for scalability.
- Conducted A/B studies to help with product decisions.
- Clustered user behavior into distinct and comprehensible segments.
- Conducted and internally published the app's virality to report product success and direct product decisions.
- Data ScientistPlayHaven2012 - 2014
Technologies: Linux, Python, Github, R, Hadoop Streaming
- Modeled and predicted user behavior in mobile games. Core projects included churn prediction and user path prediction.
- Managed relations between data science and engineering to catalyze productization of initiatives.
- Conducted ad hoc advanced analytics to assist in product decisions and to seed ideas for future data modeling.
- Rebuilt system logs: Solved for errors in observed device identifiers and marked invalid log entries as such. More precisely, the task was to write an iterative mapreduce algorithm to solve for all connected components in a several-billion node network using Hadoop Streaming and Python.
- Recruited, trained, and managed small teams of interns to assist with projects.
- Data Miner, Software Engineer, and Data EngineerNike Sport Research Lab2011 - 2012
Technologies: C++, Python, MySQL, Wolfram Alpha
- Demoed data mining.
- Defined roles for new full-time data miners in a lab.
- Created a database architecture to centralize the lab's data collection and analysis.
- Worked with researchers to import their personal research data into a consistent format.
- Liaised with lab researchers and the Wolfram team to build the centralized database.
- Research AssistantPortland State University - Teuscher Lab2010 - 2011
Technologies: Linux, C++, ParadisEO, Evolutionary Algorithms, Traffic simulations, Complex network analysis.
- Built an evolutionary algorithm in C++ using the library ParadisEO to evolve complex networks.
- Wrote a network evaluation utility to simulate traffic and calculate other metrics on networks representing massively parallel processors with non-traditional interconnections.
- Built out and documented the experimentation process to enable fellow researchers within and outside of the university to use my framework.
- Conducted experiments relating the properties of links to the types of networks it would optimally be used in.
- Wrote a thesis on creation of a framework and the results of initial experiments.