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Data Scientist

Location:
San Francisco, CA
Salary:
100000-120000
Posted:
October 23, 2017

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Resume:

Valerie Amoroso

*******.*******@*****.*** 570-***-****

www.linkedin.com/in/valerie-amoroso Github: vamoroso SUMMARY

DATA SCIENTIST WITH A STRONG ABILITY TO COMMUNICATE TO BOTH TECHNICAL AND NON-TECHNICAL AUDIENCES, DRAWING FROM AN EXTENSIVE EDUCATION EXPERIENCE TO DECOMPOSE COMPLEX PROBLEMS INTO SIMPLE SOLUTIONS.

EDUCATION

UNIVERSITY OF

SAN FRANCISCO

MS IN ANALYTICS

June 2017

WILKES UNIVERSITY

MS IN EDUCATIONAL TECHNOLOGY

June 2011 Wilkes Barre, PA

Cum. GPA: 4.0

PENN STATE UNIVERSITY

BS IN MATH EDUCATION

May 2008 University Park, PA

Cum. GPA: 3.96

COURSEWORK

GRADUATE

Advanced Machine Learning

Web Scraping and API Connections

Time Series Analysis

SQL/NoSQL Databases

Spark Distributed Computing

Natural Language Processing

Experimental Design

SKILLS

PROGRAMMING

Python (Scikit-Learn, Pandas, NumPy,

SciPy, Flask) • R • Spark • Bash

Object-Oriented Programming

DATABASE

MySQL •Cassandra • MongoDB

VISUALIZATION

Tableau • Shiny • ggplot

TESTING

A/B • Factorial Design

Multi-Armed Bandit

TOOLS

GIT • AWS • SCRUMmethodology

CERTIFICATIONS

Google Analytics IQ

EXPERIENCE

SIMPATICAMEDICINE DATA SCIENCE INTERN

January 2017 – June 2017 San Francisco, CA

• Role was to derive quantifiable information from several terabytes of genomic data to drive DNA-based medical diagnostic tools.

• Reduced computation time on state-of-the-art DNA reconstruction algorithm by adapting it to a distributed computing framework via Pyspark.

• Built a data pipeline to streamline the process of reconstructing reported DNA sequences to find the best matches in the genome for use in ML and AI models. NOTABLE PROJECTS

VUNGLE CLICK THROUGH RATE PREDICTION CLASS PROJECT

• Built logistic regression model in Python to predict click through rates of mobile advertisements using Scikit-learn on training set of 20M observations.

• Achieved a 7% improvement over the baseline log loss by creating new features and used feature selection to reduce dimensionality. CANADIAN BANKRUPTCY RATES CLASS PROJECT

• Created a forecasting model in R to predict future Canadian bankruptcy rates.

• Achieved an RMSE of .0028 by cleaning the data to remove seasonality and trend and implementing an Arima model with external regressors. MATH EDUCATION EXPERIENCE

GREAT VALLEY HIGH SCHOOL MATHEMATICS TEACHER & COACH August 2014 – June 2016 Malvern, PA

• Created the curriculum for a Python course that highlighted important programming functions utilized in AP Computer Programming and C++.

• Taught Algebra 1, Geometry, and Computer Programming.

• Track and Field Pole-vaulting coach helping a pole-vaulter qualify for State Championships.

21ST CYBER CHARTER SCHOOL MATHEMATICS TEACHER

April 2013 – August 2014 Exton, PA

• Taught Algebra 1, Algebra 2, Accounting, and Pre-Calculus. LINGANORE HIGH SCHOOL MATHEMATICS TEACHER & COACH August 2008 – April 2014 Frederick, MD

• Taught Applications of Algebra & Geometry, Algebra 1, Algebra 2, Algebra 3, Geometry, Pre-Calculus with Trigonometry and Probability & Statistics.

• Coached Cross-country, Indoor & Outdoor Track.



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