Machine Learning, Tableau, SQL, NLP, Pandas, Seaborn
Resume:
NEIL LIBERMAN
Data Scientist
Santa Clara, CA
****.********@*****.***
nliberman.github.io/portfolio
ABOUT
Background in economics and statistics to accompany proficiency with Python. Have worked on real world problems implementing supervised and unsupervised machine learning models. Driven by an unrelenting desire to improve my technical proficiency and help influence outcomes of positive change.
EXPERIENCE
General Assembly, Washington, DC
Data Science Immersive Nov. 2016 - Feb. 2017
● 700+ hours of data science training including 40 labs and 6 projects.
● Strong emphasis on both supervised and unsupervised machine learning models which include linear and logistic regression, support vector machines, random forests, K Nearest Neighbors, DBSCAN, K Means Clustering, amongst others.
● Additional focus on statistics and linear algebra to provide a core understanding for models used.
Keyes Law Firm, LLC, Baltimore, MD Finance and Administration
Feb. 2012 - Nov. 2016
● Contributed to designing the company’s settlement tracking system in excel.
● Scoured records to find unrecouped funds from partner law firms.
● Communicated with co-counsel daily to handle administrative tasks and unresolved issues.
● Took initiative to resolve many tracking flaws and information transfer issues the firm had implemented before my arrival. This included pushing to implement an ftp file transfer system.
EDUCATION
General Assembly, W ashington, DC
Data Science Immersive Nov. 2016 - Feb. 2017
University of Maryland, College Park
B.A. Economics 2008-2012
SKILLS
Python
SQL
Pandas
Machine Learning
Tableau
Git
Web Scraping
Natural Language Processing
DATA SCIENCE PROJECTS
Basketball Analytics scraped
NBA data to find correlations
to offensive efficiency, leading
to conclusion on optimal shot
locations and player
development goals.
Iowa Liquor Sales used liquor,
population, and income data to
advise where an entrepreneur
would be best served to open a
liquor store.
Data Science Salaries scraped
data science salaries to
determine which keywords are
most predictive of high
salaries.
West Nile Virus used weather
data to predict which mosquito
traps in Chicago would contain
West Nile Virus.
Bayesian Analysis of
Terrorism used bayesian
analysis to compare two South
American populations.
Contact this candidate