Allen Gary Grimm

Allen Gary Grimm

Portland, United States
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Allen Gary Grimm

Allen Gary Grimm

Portland, United States
Member since October 17, 2014
Fascinated by the intersection of abstraction and reality, Allen found his calling in data science. He seeks new ways to empower decision making with data. With his Masters of Science degree in Computational Intelligence and experience in data mining and predictive modeling, his speciality is in clustering, modeling, and predicting user behavior.
Allen is now available for hire
  • Python, 5 years
  • iPython Notebook, 3 years
  • Decision Trees, 4 years
  • Evolutionary Algorithms, 4 years
  • Neural Networks, 4 years
  • Random forests, 3 years
  • C/C++, 3 years
Portland, United States
Preferred Environment
Linux, Python, Git
The most amazing...
...thing I've coded is an evolutionary algorithm to grow complex networks representing massively parallel processors to research the potential of new wire types.
  • Senior Data Scientist
    2014 - 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.
    Technologies: Python, Django, Git, Haystack, Solr, SQLAlchemy, Django REST Framework, HTML/JavaScript/Angular
  • Data Scientist
    Simor, via Grimm Science
    2014 - 2014
    • 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.
    Technologies: Python, MS SQL Server, Recommendation algorithm
  • Data Scientist
    Cloudability, via Grimm Science
    2014 - 2014
    • 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.
    Technologies: Python, R, Holt Winters
  • Senior Data Scientist
    Sovolve, via Grimm Science
    2014 - 2014
    • 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.
    Technologies: Linux, Python, PostgreSQL, Neo4j, Mixpanel
  • Data Scientist
    2012 - 2014
    • 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.
    Technologies: Linux, Python, Github, R, Hadoop Streaming
  • Data Miner, Software Engineer, and Data Engineer
    Nike Sport Research Lab
    2011 - 2012
    • 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.
    Technologies: C++, Python, MySQL, Wolfram Alpha
  • Research Assistant
    Portland State University - Teuscher Lab
    2010 - 2011
    • 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.
    Technologies: Linux, C++, ParadisEO, Evolutionary Algorithms, Traffic simulations, Complex network analysis.
  • Portland Data User Group (Other amazing things)

    I founded and curently run the most well-attended data meetup in Portland and frequently partner with many of the other meetups to co-host events. The first meeting started with me presenting decision trees to 15 people in a small conference room at a floundering startup on decision trees. Now, the at-least-monthly meetups see between 40 and 60 people, many of which are practicing data scientist, and have covered topics from neural networks in a notebook to random forests at scale using spark to basic EDA in R to more advanced data modeling in R.

  • Churn Precition with Graphical Models (Development)

    My flagship project at the job that turned me from a data miner to a data scientist. Slides from this and other presentations that I've done can be found here:

  • Trials and Tribulations of a Data Scientist (Other amazing things)

    My blog on data science. I plan to grow it into a stand-alone resource for data science education including everything from business to theory and execution.

  • An Exploration of Heterogeneous Networks On Chip (Development)

    My thesis, which explored the relation between the properties of links and the properties of optimally built networks.

    Citation and other metadata are available here:

  • Data Science Workshops (Other amazing things)

    A local meetup that I helped to launch for scientists to collectively share data science knowledge in the form of monthly workshops.

  • Discrete Multivariate Modeling Simulator (Development)

    The most recent sample of code that I own and can share. It is to become an open source version of Occam3 (, the modeling technique I used for Churn Prediction.

  • Python Best Practices and Tips by Toptal Developers (Publication)
    This resource contains a collection of Python best practices and Python tips provided by our Toptal network members.
  • Languages
    Python, SQL, HTML, JavaScript, C/C++, R, Octave, MATLAB, CSS
  • Libraries/APIs
    Scikit-learn, matplotlib, Django ORM, SQLAlchemy, pandas
  • Tools
    iPython Notebook, Haystack, GitHub, Apache Spark, Apache Solr, Git, Vagrant, Apache Storm, Occam3
  • Misc
    Decision Trees, Neural Networks, Markov model, Evolutionary Algorithms, Random forests, Graphical models, Simulated annealing, Regression, SVMs
  • Frameworks
    Django, Flask, AngularJS, Hadoop
  • Paradigms
    Agile Software Development, Test-driven Development (TDD)
  • Platforms
    Linux, Mac OS X, Windows
  • Storage
    MySQL, PostgreSQL, HDFS
  • Master of Science degree in Electrical Engineering
    Portland State University - Portland, Oregon
    2009 - 2011
  • Bachelor of Science degree in Electrical Engineering
    Gannon University - Erie, Pennsylvania
    2005 - 2009
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