Christopher Caldarella

Portland, MAINE ·

Data Scientist and Software Engineer with 6+ years of experience in Information Technology. I have experience with and a thorough understanding of Python as well as use of Python Data Analytics Libraries with a proficiency in Exploratory Data Analysis and Cleaning Data. I am fascinated by a good challenge, and I am always willing to dive into a problem to look for a great solution.

Skills

Data Science
  • Python
  • NumPy
  • Pandas
  • Scikit-Learn
  • MatPlotLib
  • Seaborn
  • OpenCV
  • SciPy
  • SpaCy
  • Tensorflow
  • Keras
  • SkTime
  • statsmodels
  • Plotly
  • Apache Spark
  • Dask
  • Scala
  • Folium
  • Neural Networks
  • Modeling
  • Data Visualization
  • Natural Language Processing (NLP)
  • Regression
  • Classification
  • Feature Engineering
  • Computer Vision
  • Transfer Learning


Software Development
  • Python
  • C#
  • HTML 5
  • CSS 3
  • JavaScript
  • Git
  • SQL
  • PostgreSQL
  • Relational Databases
  • JSON
  • XML
  • YAML
  • Docker
  • Selenium
  • Beautiful Soup
  • Ruby
  • PyTest
  • R
  • Bootstrap
  • jQuery
  • Flask
  • Heroku
  • Web Scraping
  • OOP


Tools
  • Jupyter Notebook
  • Google Colab
  • Anaconda
  • DataBricks
  • VS Code
  • Visual Studio
  • GitHub
  • MS Office
  • MS Excel
  • MS Word
  • MS PowerPoint
  • MS Outlook
  • Bash
  • GNU nano
  • Batch file
  • PowerShell
  • SharePoint
  • PowerApps
  • Amazon Web Services
  • AWS S3
  • AWS EC2
  • AWS Route 53
  • AWS CloudFront
  • Windows
  • Raspberry Pi OS (Raspbian)
  • Ubuntu Linux
  • Debian Linux


Projects

Face (and Object) Tracker

Track objects using a Machine Learning and a Raspberrry Pi

Is it possible to track a person and their movement with a moving camera? I explored this with a Raspberry Pi and moving camera, and possibly exploring the idea of tracking a toddler (my son).

Using a Raspberry Pi and the Pimoroni Pan-Tilt HAT, I was able to utilize OpenCV and its many capabilities to track Objects (including face-detection). I was able to leverage the use of a Haar Cascade algorithm as well as YOLOv4-tiny (with the Darknet Distibuted-Neural-Network) to accomplish this, as well as create a User-Interface for easy interaction.

View the GitHub repository

View the Presentation Deck

Hotdog/Not-Hotdog

Convolutional Neural Net that predicts whether or not an image is a Hotdog

Inspired by the HBO Series, Silicon Valley, this is a re-creation of Jian-Yang's infamous Hotdog/Not-Hotdog App. This app uses a convolutional neural net (CNN) that can run a prediction on whether a picture contains an image of a hotdog or not.

View the GitHub repository

Try the App!

Reddit Classifier Using Natural Language Processing

Use NLP to compare text from two Sub-Reddits

I pulled textual-data from two similar subreddits using my webscraping skills, and compared the two data-sets using Supervised Machine Learning. I utilized a Bayesian model, among other models, to decipher where the entry came from, and analyzed the results to deduce which model performed best.

The two subreddits used are the "AMA" subreddit and the "AskReddit" subreddit. It is worth noting that I removed some data to make it more challenging for the Machine Learning Algorithm to make a decision.

View the GitHub repository

View the Presentation Deck

Air pollutants and Air Quality Index Analysis

Team Project exploring Time Series and using Linear Regression for Data Analysis

Through exploratory analysis of CDC and EPA data we wanted to evaluate a model that could be helpful for analyzing air pollutants with the thought of creating information for people with respiratory illness.

Knowing that increasing Air Quality Index (AQI) can negatively impact people with respiratory illensses, we wanted to evaluate the realtionship with air pollutants, temperature, day of the week, and month to see if we could identify any relationship to overall daily air quality data (from the EPA website).

View the GitHub repository

View the Presentation Deck

Electricity Consumption in North Carolina

A 6-hour challenge where I used Forecasting to make a Predictive-Model

Looking at electrical usage data from previous years, I used Forecasting to make a Predictive-Model that predicts Electrical consumption in North Carolina. I selected North Carolina because North Carolina appears to be the most average State out of the whole United States, based on this 2016 article from Business Insider. This was mostly completed within 6 hours (with a few caveats clearly outlined in the repository ReadMe file).

View the GitHub repository

View the Presentation Deck

Experience

Data Scientist Fellow

General Assembly
  • Successfully completed 480+ hours of expert led instruction in Data Aggregation, Cleaning, Analysis, and Data Engineering and hands-on learning of Python and the fundamentals of many data-analysis libraries, including some of the industry's most in demand technologies.
December 2020 - March 2021

Staging Specialist

NCR - Northeast Depot
  • Led hardware and software upgrades for Northeast Depot, a storage, staging, and shipping site for Restaurants and bars in the Northeast region
  • Created tools in Python to assist with migration to new software for On-Time delivery
December 2020 - March 2021

Escalation Technician / Customer Engineer II

NCR - Rocky Mountain
  • Led training and served as escalation point for technicians at all levels including new hires
  • Completed the Qdoba Software Upgrade project by supporting the client through a company acquisition and delivering outstanding customer service.
February 2019 - November 2020

Reconciliation Specialist / Installation Specialist

BEC
  • Maintain credit-card processing environment to review and compile credit card data while fixing Errors in non-cash financial records, determine financial loss, and perform reconciliations
  • Assist Major Account Clients with issues and delegating such projects as Major Accounts Technician and Communicate progress of client-issues to Major Accounts groups
  • Created Automated Report-Forwarding tool in C# which helped Product Managers and increased Help Desk productivity with its easy to use User Interface, and simple backend functionality
July 2014 - February 2019

Cook I/Learning Coach

Elway’s at the Ritz Carlton
  • Cook 1 at Elway's Steakhouse, located inside the Ritz Carlton Hotel in Denver, Colorado.
  • Outstanding performance on Broil, Sauteé/Fry, and Pantry Stations
  • Assisted with large party's and events both with Elway's restaurant and the Banquets Team
July 2008 - July 2014

IT & Web Development

Deerwoods Real Estate Management
  • Setup domain and website with an Internet Domain Registrar using HTML, CSS, Javascript, ASP, and MS-SQL.
  • Set up conference phone-system and maintained local network.
Dec 2007 - July 2008

Education

General Assembly


Certification Data Science Immersive
2021

Scrum Alliance


Certification Scrum Master

Certification Scrum Product Owner
2020

Rutgers School of Engineering


Bachelor of Science Electrical and Computer Engineering
2004

Recognition

  • [Chris Caldarella] is always available to help even when he really isn’t. He is constantly expanding his knowledge to better himself and the company; making numerous applications to make our lives a little easier.
    – 11/30/2018, Employee of the Month Nomination at BEC

  • [I nominate] Chris Caldarella for his dedication to the Qdoba 6.7-15.1 project and always having [our] back with EDC questions and [Automated-Report-Forwarding] issues. Chris also came up with a batch file to help alleviate some of our ATG issues and has been a huge asset to the team jumping in where needed.
    – 10/31/2018, Employee of the Month Nomination at BEC

  • [I nominate] Chris Caldarella: [For his] "Help with [Automated-Report-Forwarding] and [he] always finds the time to help or teach. [He] Also has made a page in the WIKI that helps the whole desk. His attitude is always kind and smiling.”
    – 7/25/2018, Employee of the Month Nomination at BEC

Interests

Besides hanging out with my wife and son, I enjoy cooking, listening to music, and playing music; I played bass in a band in Denver, Colorado before moving to Maine.

I also play guitar, and I am currently trying to learn to play drums and piano in my spare time.

I love reading, but I have recently turned to listening to audiobooks and the occasional podcast.

I have a deep passion for learning especially about technology, and figuring out how things work.

RESUMÉ