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Jacob Press
Welcome to my website!
My name is Jacob Press. After a decade of career twists and turns I find myself working as a machine learning engineer. I think my diverse set of experiences and interests gives me a unique perspective that makes me valuable member of any team I find myself a part of. I hope this website helps you get a sense of who I am both professionally and personally.
Experience
2021-Present
ML Engineer
American Express
2020-2021
Data Scientist
IBM
2017-2019
Entrepreneur
Fulfyll
2014-2017
Financial Analyst
BAE Systems
Technical Skills
Python
Docker
Fast API
Javascript
PostgreSQL
MongoDB
Scikit-learn
Pandas
Numpy
Tensorflow
Selenium
Ubuntu
Git
HTML
CSS
React
GCP
Azure
AWS
Microsoft Office
Canva
Wordpress
Python
Docker
Fast API
Javascript
PostgreSQL
MongoDB
Scikit-learn
Pandas
Numpy
Tensorflow
Selenium
Ubuntu
Git
HTML
CSS
React
GCP
Azure
AWS
Microsoft Office
Canva
Wordpress
My Philosophy
My favorite podcast is called Philosophize This! by Stephen West. He finishes many episodes by saying "Thank you for wanting to know more today than you did yesterday."
To me, life is this complicated miracle that most of us humans are just doing our best to figure out. Everyday I try to be a little more equipped to thrive in the areas of life that matter most to me. These include broadening my knowledge and perspective through learning, building intimate relationships, taking care of my physical and mental health, and doing; whether that be coding this website or trying something new.
Also core to my philosophy is that life is not a straight line and the world is far too complex for any one person to comprehend. With these guiding principles in mind I try to leave a positive imprint on every interaction and give both myself and others grace and kindness in the face of our mistakes and shortcomings.
Personal Interests
New York Jets
- TV
- Sports
- Football
Severance
- Television
- Entertainment
- Thriller
3Blue1Brown
- Youtube
- Learning
- Mathematics
Education
2010-2014
Bachelor of Science (MIS, Finance)
Binghamton University
2019-2019
Data Science Bootcamp
Galvanize
2020-2020
Data Science Apprenticeship
IBM
Projects
Created NBA stat that values players based onthe context of their teammates. Used python and sql to get, store, compute, and display a variety of player and team info related to Wins Contributed including creating supervised and unsupervised learning models to predict similar players and team wins for the upcoming season.
- Supervised ML
- Unsupervised ML
- SQL
- Python
- Matplotlib
- Scikit Learn
- Pandas
- Numpy
Built this website! This iteration uses React for front end but previous iterations used Flask as the server and a python front end
- React
- HTML
- CSS
- Javascript
- Material Ui
- Flask
- Heroku
A bot that scrapes data and predicts an optimal daily fantasy lineup with the goal of winning 1 on 1 contests greater than 57% of the time. Used selenium to scrape data, python to store and analyze data, and machine learning to predict the best lineup.
- Selenium
- Python
- Time Series Analysis
- MongoDB
- XGBoost
- Pandas
- Numpy
Explored the history of the United States through the lens of presidential speeches. Uses many AWS nodes to scrape data quickly; NLU techniques and data visualization to display insights from speeches; and Unsuperivsed ML to create similarity clusters for Presidents
- AWS
- Matplotlib
- Python
- Seaborn
- SQL
- NLTK
- Tensorflow
- Spacy
- Plotly
- SciKit Learn
- BeautifulSoup
A group project from the data science bootcamp where we built an application that leveraged a self-made fraud model to predict the likelihood of fraud in a transaction. We used Flask to create the front end and back end and used supervised machine learning to create the model. We also used MongoDB to store the data.
- Python
- Flask
- Bootstrap
- HTML
- CSS
- MongoDB
- Scikit Lean
- Supervised ML
Created NBA stat that values players based onthe context of their teammates. Used python and sql to get, store, compute, and display a variety of player and team info related to Wins Contributed including creating supervised and unsupervised learning models to predict similar players and team wins for the upcoming season.
- Supervised ML
- Unsupervised ML
- SQL
- Python
- Matplotlib
- Scikit Learn
- Pandas
- Numpy
Built this website! This iteration uses React for front end but previous iterations used Flask as the server and a python front end
- React
- HTML
- CSS
- Javascript
- Material Ui
- Flask
- Heroku
A bot that scrapes data and predicts an optimal daily fantasy lineup with the goal of winning 1 on 1 contests greater than 57% of the time. Used selenium to scrape data, python to store and analyze data, and machine learning to predict the best lineup.
- Selenium
- Python
- Time Series Analysis
- MongoDB
- XGBoost
- Pandas
- Numpy
Explored the history of the United States through the lens of presidential speeches. Uses many AWS nodes to scrape data quickly; NLU techniques and data visualization to display insights from speeches; and Unsuperivsed ML to create similarity clusters for Presidents
- AWS
- Matplotlib
- Python
- Seaborn
- SQL
- NLTK
- Tensorflow
- Spacy
- Plotly
- SciKit Learn
- BeautifulSoup
A group project from the data science bootcamp where we built an application that leveraged a self-made fraud model to predict the likelihood of fraud in a transaction. We used Flask to create the front end and back end and used supervised machine learning to create the model. We also used MongoDB to store the data.
- Python
- Flask
- Bootstrap
- HTML
- CSS
- MongoDB
- Scikit Lean
- Supervised ML
Contact
