Adam Parente

Intro

I am currently a data science student at Thinkful building on a strong international relations background from the University of Chicago and American University. Data science is a natural transition given I'm already experienced in connecting broad concepts and big ideas with specific, observable metrics. This change was motivated by a search for a more engaging career. Skills include Python, statistical analysis, experimental design, data cleaning/exploration, machine learning, customer service and teamwork. Check out my work.

Work

To practice working with regression models and sklearn pipelines, I explored predictors of census tract mortgage approval rates, notable minority population % and income.
Neighborhood Mortgage Approval Rates

As an example of A-B Testing, I assessed the impact of a famous Mexican welfare program from the late 1990's.
Progressa Welfare Impact

As an example of Clustering Technique, I attempted to cluster stocks by their quarterly fundamentals.
Stock Fundamentals Clustering

I attempted to apply neural networks to trying to predict stock price movements.
Stock Prediction Attempt

About

I worked for the federal government for two years before leaving to pursue a transition to data science. While I was successful in my position, receiving praise from management and receiving an offer for a promotion, I found myself getting further from my aspirations and interests despite nominally connecting with my subject domain. I decided a career in data science would be the best choice to reengage with my favorite parts of my education in international relations.

-High level conceptualization: My most distinguishing feature is my capacity to reconcile abstract prompts with observable metrics. This was the fundamental skill of my college education spent reading, evaluating and generating different models and empirical methodologies to answer questions with immense underlying complexity. As an example, one of my projects was exploring low level support in intrastate conflict, which was published in the student journal. Despite being a newcomer to data science, my social science background demonstrates a strong analytical background that takes time to acquire.

-Technical proficiency: Since my decision to change careers, I’ve been building up a portfolio of projects to demonstrate core skills. I am competent with the entire data science workload, from data gathering to model implementation. My Python expertise is demonstrated by effective use of key modules like Pandas, Scikit-learn and Keras/Tensorflow. My latest project has been to explore deep learning model creation and apply it to stock data, although the results have been less than promising. I still have a lot to learn, but that aspect of perpetual growth is one of the attractive aspects of data science.

-Experience in customer service: From previous experience as a transportation security officer and a banquet server, I bring experience in being professional and courteous, even with disagreeable individuals. Just like with TSA pat-downs, I can be sure to communicate key tasks beforehand and make appropriate accommodations.

I’m currently seeking data science or data analyst positions so if you think I would be a good fit for your company, please contact me directly at adam.m.parente@gmail.com

Key Skills: data mining, data analysis, data cleaning, Python, SQL, Excel, research, modeling, machine learning, A/B testing, categorical inference, forecasting, deep learning

Contact

• fa-linkedin
• GitHub

Elements

i = 0;

while (!deck.isInOrder()) {
    print 'Iteration ' + i;
    deck.shuffle();
    i++;
}

print 'It took ' + i + ' iterations to sort the deck.';