Start-up seeking NLP developers (Part 2)
Portée du projet
Catégories
Visualisation des données Analyse des données Modélisation des données Développement de logicielsCompétences
parsing energetic willingness to learn natural language processing (nlp) computer scienceNumber of positions available: up to 4
Our team is seeking up to four energetic NLP(natural language processing) developers who are passionate and creative. We want these students to be entrepreneurial and willing to learn from ~30 years of combined experience. The students will be responsible for implementing functions in our dev environment and Google Collaboratory.
The project:
We are going to provide each of the four student with a list of links and the sections we want algorithmically parsed, using natural language processing techniques. Our dev team will work closely and train the student(s) on how to accomplish this. The students will then execute the algorithmic parsing of the provided links. We are going to start out slow, and ramp up, as the project progresses.
This is an incredible opportunity to build your resume and portfolio.
If you are in your 3rd/4th year of your Computer science, engineering or related program and are looking for an incredible opportunity this is it.
Does bringing organization to chaos excite you? If so, that is what you will be doing while in this internship. The data that we want parsed is not structured hence it is extremely messy, we want to put order to it. We will give you the training to organize this and we will let you solve these problems at scale.
As always we will offer at least 15hrs of mentorship and supervision to our students. This will be detailed training and "How to" modules. Please note that this is a remote internship.
À propos de l'entreprise
Ubineer is a leading AI financial technology company focused on delivering productivity to financial decision makers. Our goal is to be the primary source for knowledge management, collaboration and insights in the investment industry. Our mission is to help financial decision makers optimize the quality and speed of their investment lifecycle.