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Resumegoogle2012

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Mathematical biologist seeking a career transition towards a data scientist role with a tech company. Adept with complex data analysis and visualiza- tion. Experience applying statistical analysis to address practical problems and to support decision-making. Independent and self-motivated team mem- ber accustomed to balancing multiple projects and making efficient use of my time and the time of others. Strong communicator.
UNIV. OF CALIFORNIA SANTA CRUZ — PHD, 2007Emphasis in Mathematical BiologyHonor: Sea Grant/NMFS Graduate Fellowship in Population Dynamics, 2002–2005Honor: U.C. Dean’s Cota-Robles Graduate Fellowship, 2002–2004 COLLEGE OF THE ATLANTIC — BA, 1999Emphasis in Environmental Monitoring and Management SELECTED ANALYTICAL METHODS APPLIED IN MY RESEARCH Ordination, Clustering, Linear Regression, Logistic Regression, Generalized Linear Regression, Multilevel/Hierarchical Modeling, Optimization, Stochastic Differential Equations, Numerical ODE solvers, ODEs, Time-Series Analysis STATISTICAL CONSULTANT AND FOUNDERSignal to Noise Consulting, Pasadena, California POSTDOCTORAL RESEARCHERNorthwest Fisheries Science Center, NOAA, Seattle, Washington Honor: National Research Council Postdoctoral Fellowship, 2007–2011 GRADUATE STUDENT RESEARCHERDept. of Applied Math and Statistics, Univ. of California Santa Cruz R FOR BEGINNERSGiven at NOAA-Fisheries in Seattle 2010, 2011Given at PNW-USFS, Corvallis, Oregon 2011A two day workshop developed by myself to introduce biologists to R, and to INTRODUCTION TO LATEX FOR THESIS WRITINGGiven at ESA annual meeting 2009, 2010A one-day workshop developed by myself to introduce graduate students to JUVENILE SALMON HABITATSeattle Lab, NOAA-Fisheries/Signal to Noise Consulting I simulated juvenile distributions in a stream network using a system of sto- chastic differential equations. I used a k-means clustering algorithm to iden- tify when the spatial distributions of different juvenile groups merged. In an- other project, I applied several ordination analyses to a dataset describing salmon habitat. There were over 32 variates that were expected to organize into a few multivariate descriptors of habitat quality. Using several ordination methods, I was able to show that the expected patterns were in fact not pre- sent, and uncover some of the reasons for this behavior. In another, exten- sive project, I prepared for analysis a large data set of spatial y distributed fish and habitat information. I conducted an extensive exploratory analysis and guided client scientists through a modeling process. Ultimately, I imple- mented a zero-inflated, multilevel logistic regression model using the lme4 package in R. Model results are being applied to endangered species man- DATA FLOW IN NATURAL RESOURCES MANAGEMENTSeattle Lab, NOAA-Fisheries In col aboration with a database manger col eague, we conducted a survey of natural resource scientists that work with monitoring data. We used the sur- vey results to il ustrate how problems in data management were negatively impacting science productivity throughout the natural resources field. Our final report presented several solutions gleaned from a review of the litera- MATERNAL EFFECTS IN ROCKFISHUC Santa Cruz/Santa Cruz and Seattle Labs, NOAA-Fisheries For my PhD, I developed an extensive simulation based on a novel popula- tion model for maternal effects in rockfish. The model was a non-linear sys- tem of ODEs. I wrote a numerical solver based on a Predictor-Corrector algo- rithm. I simulated hundreds of population trajectories and summarized the outcomes with complex graphics, linear regression and time series analysis. SPECIES-ABUNDANCE CURVES IN TROPICAL REEF FISHSeattle Lab, NOAA-Fisheries I supported the work of a col eague by developing a novel model for species- abundance curves. The model was based on a summation of the probability density function of the multinomial distribution. This was used to identify sites with unusual y large diversity from a database of tropical reef fish.
STOCK ASSESSMENTSanta Cruz Lab, NOAA-Fisheries In Fisheries Science, a stock assessment is an extensive statistical analysis performed by teams to assess the population status of a managed fish spe- cies. I supported the assessment of Shortbel y Rockfish by providing several alternative models and calculations for the rate of natural mortality. I pre- pared the data for the assessment of California Halibut. Data prep included several analytical steps, including applying a GLM-based filtering tool. The initial data for this assessment was too large to load into the R workspace. I developed several strategies for performing analyses on data subsets and pooling results together for a summary data set. This was my first experience

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