Sam Chakerian

Seattle, WA · (253) 677-6329 · samchakerian@gmail.com

Data specialist with psychology background. Seeking to directly impact efficiency and enable more rational, powerful decision-making. In my free time, I pursue manual and quantitative trading. Strengths include Python, data visualization, and making statistical insights accessible to non-technical users.

Skills include Python, machine learning (scikit-learn, Keras), data visualization (Tableau, Python libraries), statistical analysis (pandas, Excel, Sheets), automation (Selenium), version control (Git, Github), Google APIs (Sheets, Drive, Maps), SQL, cloud computing (AWS), and non-technical writing.

Resume (January 2019)


Projects

Algorithmically Detecting Technical Chart Patterns

patterns


Notebook and Medium article demonstrating how to programmatically find technical chart patterns in stock data, visualize results, record returns, and implement trade signals using Python and the Alpaca Trade API.

Capstone: Predicting Solar Irradiance

DATA SCIENCE IMMERSIVE, GENERAL ASSEMBLY
solar


Modeled solar irradiance for the Los Angeles area. Used LSTMs with historical irradiance, weather, and satellite data to predict trends at one day and one week projections.

  • Used LSTM model (recurrent neural network) to predict 1 day and 1 week future solar irradiance for the Los Angeles area.
  • Used over 2 million points of one-minute resolution solar and weather data from 2010-2016.
  • Extended project with satellite imagery and convolutional neural network model running on AWS.
  • Skills used: Python 3, pandas, DASK, matplotlib, Keras, AWS
# Keras   # Python 3   # Time series   # AWS

Time Series and Geospatial Modeling: Chicago West Nile Virus Prediction

DATA SCIENCE IMMERSIVE, GENERAL ASSEMBLY
chicago

Group project predicting spread of West Nile Virus in Chicago from 2011 - 2013, using City of Chicago and local weather datasets. Utilized time series, geospatial, and weather data with clustering and multiple models to find the most accurate predictions.

  • Predicted spread of West Nile Virus in Chicago, using City of Chicago and local weather datasets (Kaggle competition).
  • Used time series, geospatial, and weather data with clustering and scikit-learn models to find most accurate model.
  • Predicted WNV positive areas with 65% accuracy, generalized results to cost-benefit analysis and budget for spraying.
  • Skills used: Python 3, pandas, matplotlib, time-series, geospatial, clustering, scikit-learn, Tableau.
# Geospatial   # Clustering   # GridSearch   # Python 3   # Time series    # Tableau   # Bokeh   # Git   # Scikit-learn

Multiple Linear Regression: Ames Iowa Housing Price Prediction

DATA SCIENCE IMMERSIVE, GENERAL ASSEMBLY

Kaggle competition: Predicted housing prices for dataset of over 2,000 houses and 85 features, scoring 87% accuracy. Used alternative datasets, scikit-learn, and multiple statistical validation techniques.

  • Predicted housing prices for dataset of over 2,000 houses and 85 features, scoring 87% accuracy.
  • Used alternative dataset, feature selection, and regularization to get best score.
  • Skills used: Python 3, pandas, scikit-learn, seaborn.
# Python 3   # Scikit-learn   # Feature selection   # Regularization

VIX Scraper and Analysis

Self

Calculated the Volatility Index value from SPX options chains scraped on Yahoo!Finance.

  • Calculated the Volatility Index from SPX options chains scraped on Yahoo! Finance.
  • Translated VIX equation from CBOE whitepaper into Python code and validated by comparing with realtime VIX value.
  • Skills used: Python 3, web scraping, pandas, domain research.
# Scraping   # Control flow   # Math




Education

General Assembly Seattle

Data Science Immersive
Rapidly developed skills in data science, Python, machine learning, and predictive modeling over 12 week course.
July 2018 - October 2018

University of Washington Tacoma

B.A. Psychology
September 2012 - June 2014

Skills

Programming Languages & Tools
  • Python 3.6
  • Pandas
  • Scikit-learn
  • Keras
  • Matplotlib
  • AWS (EC2, S3)
  • Selenium
  • SQL
  • Google APIs
  • Git/GitHub
  • Tableau

Other experience

Content and Copy Writer

Freelance

Wrote content and copy for fields including eCommerce, travel, personal finance and psychology.

January 2017 - January 2018

Driver

Alpha Distributing

Picked and delivered beer, soda, and hot sauce for local businesses, handled and reconciled payments. Great at parallel parking a box truck.

February 2016 - January 2017

Lead Bassist

Swing Reunion Orchestra

Performed double bass at gigs, monthly dances, and weekly sessions.

February 2015 - March 2017

Personal interests

I am incredibly interested in financial trading, no matter what method, timeframe, or instrument. To me, trading is an amazing cocktail of human psychology, decision-making, statistics, economics, and game theory... it never ceases to evolve and change, so there is no real way to "solve" it. I think there are many lessons to be learned from trading including more effective decision-making, restraint, patience, probabilistic thinking, and acceptance of loss.

In my free time I pursue discretionary (meaning manual) currency trading, and seek to connect local traders in my community to share ideas, lessons, and better master this amazing game!