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## Resumegoogle2012

**T**: 831.332.4596

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, 2007

*Emphasis 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, 1999

*Emphasis 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 FOUNDER

*Signal to Noise Consulting, Pasadena, California
POSTDOCTORAL RESEARCHER**Northwest Fisheries Science Center, NOAA, Seattle, Washington
**Honor: National Research Council Postdoctoral Fellowship, 2007–2011*
GRADUATE STUDENT RESEARCHER*Dept. of Applied Math and Statistics, Univ. of California Santa Cruz
R FOR BEGINNERS**Given at NOAA-Fisheries in Seattle 2010, 2011Given at PNW-USFS, Corvallis, Oregon 2011*A two day workshop developed by myself to introduce biologists to R, and to
INTRODUCTION TO LATEX FOR THESIS WRITING*Given at ESA annual meeting 2009, 2010*A one-day workshop developed by myself to introduce graduate students to
JUVENILE SALMON HABITAT*Seattle 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 MANAGEMENT**Seattle 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 ROCKFISH**UC 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 FISH**Seattle 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 ASSESSMENT*Santa 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
*Source: http://yasminlucero.net/yasmin/resume2012.pdf

Bonificación 90 años de Mutual de Seguros Tercer sorteo zona sur El miércoles 21 de octubre se llevó a cabo el tercer y último sorteo del Beneficio que en virtud de su nonagésimo aniversario entrega Mutual de Seguros a mil de sus asegurados en todo Chile, como premio a su preferencia y permanencia junto a la Corporación. 342 titulares de seguros con domicilio en las regiones sép

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