Charles Joseph

Python Developer

New York, NY

acxlzs@r.postjobfree.com

Seeking a junior/mid-level python development role, preferably in a financial/mathematical capacity. Authorized to work in the US for any employer

WORK EXPERIENCE

Freelance Python Developer

Self-Employed - New York, NY - January 2015 to Present Data Leads Project - Client wanted Python program to analyze SQL data and write to Excel spreadsheet on a weekly basis. The program helps the client track customer purchases, which type of media the customer prefers, and which products are trending overall. This project is on-going with ad-hoc charts, tables, and statistics per client business needs. Written with Python, xlsxwriter, NumPy, pandas, git. Dow Jones Industrial Average Analysis - Project examined the DJIA for the last ten years. The quantitative analysis included a look at the index values, daily log returns (to check time-varying volatility and volatility clustering), normality of log returns (to check skewness and kurtosis as compared to the normal probability density function), annualized standard deviation of the log returns (historical volatility), quantile-quantile plot of daily log returns (to further check normality), and plots for rolling mean log returns, rolling volatility, rolling correlation (252 days). Written with Python 3.5, NumPy, pandas, matplotlib, statsmodels, scipy, PyCharm. Portfolio Optimization - Simulation takes parameters for start/end date, list of stocks and their respective allocations. It uses NumPy and pandas to read and vectorize the time-series data from Yahoo Finance. Then, the data frame is appropriately normalized and put through a series of calculations with the outputs being the cumulative return, the daily return, the volatility, and the Sharpe ratio. Using matplotlib, the daily return and volatility are displayed graphically. The simulation provides an option to optimize the portfolio for maximum cumulative return and outputs this stock allocation combination. Future plans are to add user interface via Flask and JavaScript, a persistence layer, and more plotting options. Written with Python, NumPy, pandas, matplotlib, Sublime Text, git.

New on Netflix - Website pulls data from SQL database to display net Netflix listings and any associated ratings from Rotten Tomatoes. The end result is an amalgamation of scraped data to better inform the user on new, highly rated movies/shows. Future plans are to include what is leaving Netflix as well as an archive of past months. Written with object-oriented Python, Flask, SQL, Beautiful Soup, httplib2, Jinja2, HTML/CSS, Bootstrap, jQuery, Linux, Sublime Text, git.

Sabbatical

Independent Study (Software Development) - New York, NY - January 2014 to December 2014 Projects

Manhattan Real Estate Application - Application communicates with Street Easy’s RESTful API. The GET request extracts JSON data, transforms/parses it, and plots “Price vs Square Feet” by Manhattan neighborhoods. User can create custom search (e.g. bed/bath/price) to see many data points (avg sqft, avg price, avg weeks on market, etc) for their desired location. Written with Python (requests, json, matplotlib). To-Do List Application - Webpage takes user input to create a to-do list and generates a unique URL. The to- do list is stored in the persistence layer allowing the user to add, update, or delete an item at any time. Written with Python, Django, Selenium, HTML, CSS, Bootstrap, JavaScript, SQLite, Heroku, Gunicorn, git. Robotic Vacuum Simulation - A simulation to compare how many time-steps one or more Roomba-like robots will take to clean the floor of differing sized rooms using two strategies (standard movement vs. stochastic walk). Written with Python (math, random, pylab, unittest). Courses

MIT - Intro to Computer Science and Programming Using Python - Covered computation, the Python programming language, algorithms and data structures, testing and debugging, and informal introduction to algorithmic complexity.

MIT – Intro to Computational Thinking and Data Science Using Python - Examined plotting, stochastic programs, probability and statistics, random walks, Monte Carlo simulations, modeling data, optimization problems, and clustering.

GT - Computational Investing - Reviewed economic theories of investing and how to create Python programs to take advantage of them.

UW - Mathematical Methods for Quantitative Finance - Covered topics from calculus and linear algebra that are fundamental for the study of mathematical finance. Also explored the Black-Scholes model. Research Scientist

Merck (MSD) - Rahway, NJ - August 2006 to December 2013 Drug Metabolism Scientist (DMPK)

Analytical Scientific Lead for multiple drug targets: A2a receptor (Parkinson’s Disease), HDM2/MDM2

(Oncology), TACE inhibitor (Rheumatoid Arthritis), HCV NS5B (Hepatitis C). Decreased average data analysis reporting time by 40% by leveraging automation (Hamilton STAR robotics, MS Excel macros).

Reduced inventory waste by 15% through standardization of materials and Lean Six Sigma methodologies. Received numerous peer-nominated awards for exhibiting leadership behaviors, supporting team members on difficult projects, and meeting business-critical deadlines. Promoted twice: Assistant Associate Scientist (2009) Research Scientist (2012) EDUCATION

BS in Chemistry

University of Florida - Gainesville, FL

BS in Chemical Engineering

University of Florida - Gainesville, FL

SKILLS

Python (3 years), NumPy (2 years), pandas (2 years), matplotlib (1 year), Flask (2 years), Linux (2 years), HTML 5 (1 year), CSS3 (1 year), Git (2 years), SQL (2 years), SQLAlchemy (1 year), Bash Scripting (1 year), Object Oriented Programming (2 years), Design Patterns (1 year), SciPy (1 year), Statistics (1 year), StatsModels (1 year)

LINKS

http://www.github.com/cjoseph246/

http://www.linkedin.com/pub/charles-joseph/4/748/71/

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