A specialist in predictive modeling, I am happy wherever I can play with code and numbers and create streamlined, innovative models out of huge data sets. Having lived and worked abroad for five years, I have a global perspective on the software industry. I'm also fluent in Japanese and conversant in Spanish and Portuguese. In my job as the lead Predictive Modeling Scientist at the startup software company [Clear Returns][1], I further expanded my skills in machine learning with R, Python, and SPSS and creating dynamic models of complex systems. This also entailed managing multiple SQL databases with up to 4million data points each. Working with front-end developers, I created the core mathematical functionality of our award-winning software from scratch. In 2014, [we were runners-up in the Retail Week Hackathon][2]. For my postgraduate degree, I built a statistical model of the ecological effects of temperature change in the North Sea. This project involved collecting and cleaning large data sets from a variety of sources and applying novel combinations of modeling techniques. I presented my findings and statistics techniques as a speaker at the European Congress for Conservation Biology in 2012. In 2014, I completed a certificate from Johns Hopkins Bloomberg School of Public Health in Data Science and Machine Learning. This further enhanced my skills in building machine-learning algorithms, as well as visualizing complex data sets and creating apps using the Shiny package in R. Samples of my work are available on GitHub.

Business Analyst @ From August 2015 to Present (3 months) SeattleLead Predictive Modeling Scientist @ Create machine learning algorithms for award-winning online tools. Design and implement predictive models for customer behaviour based on online retail data. Collect and clean data from online retailers. Analyse and present findings from models and data using R, SQL, SPSS, SAS, NumPy, Python and Excel. From January 2013 to May 2015 (2 years 5 months) GlasgowTheoretical Ecologist and GIS Modeling Specialist @ Created predictive models of collision risk and projected bird mortality for wind farms. Generated digital maps of bird distribution and habitat types. Performed quality checks on data. Designed turbine layouts to minimise environmental effects based on predictive probability models. Developed improved modeling techniques. Presented findings on climate and ecology at the European Congress of Conservation Biology. Talk entitled '‘Anthropogenic climate change as the driver of sandeel population collapse in the southern North Sea: a bottom-up statistical analysis’ August 2012. From July 2011 to November 2012 (1 year 5 months) Glasgow, United KingdomStatistics Teaching Assistant @ Created statistics course practice material; led students in applied statistics exercises From October 2010 to February 2011 (5 months) Glasgow, UK

Certificate, Data Science @ Johns Hopkins Bloomberg School of Public Health From 2014 to 2015 Certificate, Epidemiology @ Johns Hopkins Bloomberg School of Public Health From 2014 to 2014 MSc, Statistical Modeling of Marine Ecosystems @ The University of Glasgow From 2010 to 2011 BA, Biology (Ecology), Cum Laude @ Amherst College From 2006 to 2010 Certificate, Maritime Studies @ Williams College From 2007 to 2007 Shaylon Stolk is skilled in: Predictive Modeling, Statistics, R, SPSS, GIS, Environmental Science, Offshore Wind, Marine Spatial Planning, Natural Resource..., Ecological Assessment, Marine Conservation, Python, Machine Learning, Research