Hello / Hallo

I'm Nicolas Kammerdiener

Full-Stack Developer | Blockchain Developer | Machine Learning Engineer

  • E-MAIL nicolas@kammerdiener.us
  • LOCATION Greater Atlanta Area

Download Resume

I’m Nicolas Kammerdiener. I work as a Full Stack Developer with Blockchain and Machine Learning. I’m always looking for something extremely interesting to work on and enjoy being challenged regularly.

Development Skills

AngularJS 80
ReactJS 70
ExpressJS 90
NodeJS 90
GoLang 80
Python 75
AWS 90
MongoDB 70
Hyperledger Fabric 60
TensorFlow 50
Solidity 50
Kafka 50

My Interests

  • Mountain Biking
  • Scuba Diving
  • Photography

Work Experience

Jan 2015 - Present

Owner

Kammerdiener Technologies

Web Development, Blockchain, and Machine Learning

December 2018 - Present

Full-Stack Developer

MacStadium

Work Full-Stack to create new applications for internal and external use. Work on multiple new products with new and different technologies.

Jan. 2016 - Present

IT Contractor

Black Sea Systems

Worked with multiple clients to help solve IT issues. Worked to maintain servers.

July 2018 - December 2018

Blockchain Developer

BitRail

Nov. 2017 - Jan. 2019

Full-Stack Software Engineer

CoreAlpha Technologies

Worked Full-Stack using Blockchain (Hyperledger) as a Datastore. Using React within the Front-End. Worked with a very small team in order to get a project done quickly.

Feb. 2017 - May 2018

Full-Stack Software Engineer

TraxionIO

Worked as a Full-Stack Developer throughout the entire Software Development Lifecycle. Worked to create new Applications for use within the software as well as working with Client Success to maintain current ones.

May 2012 - Feb. 2017

Technology Assistant

North Cobb Christian School

Worked closely with the Systems Administrator to help provision servers and set up Virtual Machines. Worked Closely with the Networking side to help set up the Network for the school.

Education

2018

Blockchain Developer

Udacity

2014 - 2018

Applied Computer Science Major Information Security and Assurance Minor

Kennesaw State University

2017

Deep Learning Foundations NanoDegree

Udacity

Portfolio

Carroll Daniel Construction – Internal Store

Motivo

Worked to help create the Client Facing piece forĀ Motivo. This included working with NextJS and ReactJS to build out the FrontEnd along with integrating with Auth0. This also included working with other tools including Lerna, Node, Express, and PostGresĀ in order to help complete the project.

Where Should We Drop

Where Should We Drop

This was a very simple React Native Project that was built. The purpose of this was to simply randomly select a location to drop in the popular Fortnite Game. It works on both iOS and Android.

College Football Coach Win Prediction Using a Neural Network

Predicting College Football Coach Win Percentages Using a Neural Network

In this project for my Honors Capstone I created a Neural Network that was used to predict College Football Win Percentages. The purpose was to be able to predict it over a few years to see if the coach would be able to become a better coach over time. This was interesting since it was able to utilize a simple Neural Network but it still required some effort on the data collection and preparation side of the project.

CoreIntegrate

Worked with a Blockchain Back-end to create an Employee Document Store. This involved working with Hyperledger in order to help with the data storage and a React Front-End to allow it to be worked with from a Web-App.

Traxion – Web App

Top Overview

Worked Full Stack to create a Web App. Using a Mongo Database along with a Node and Express Backend and leveraging an Angular Front End. Worked with Material Design in order to help speed up development. Worked with Infrastructure in order to deploy and help scale the application as needed. Worked closely with Client Success to make sure that the customers truly enjoyed working with the Application.

The Application is based off the Entrepreneurial Operating System (EOS) and is a methodology for helping to run your business.