You are viewing a preview of this job. Log in or register to view more details about this job.

Data Science/ Machine Learning Internship - Loveland, CO


We are looking for a Data Science Intern for our site in beautiful Loveland, CO.

 

The Data Scientist Intern will build and support predictive analytics frameworks for the company. The ideal candidate will have extensive experience in analytical, data mining and predictive tools and will identify and propose innovative solutions for various business functions.


Job Responsibilities:

  • Translate business questions and apply statistical models and analyses to answer business questions in an actionable and reproducible manner.
  • Create statistical models, machine learning and other techniques to predict customer churn, delays in order delivery, invoices that will be disputed etc.
  • Leverage SQL and other programming languages to acquire the data to analyze in ad hoc analyses.
  • Perform data profiling to identify and understand anomalies in data.
  • Automate data analysis and streamline analytical processes. 
  • Provide output based on data trends uncovered when possible. 
  • Describe the logic and implications of a data models model to all types of business partners, and work directly with them refining models and deliverables.
  • Good communication and collaboration skills, with both technical and non-technical counterparts.
  • An entrepreneurial mindset with a willingness to go the extra mile to find solution and overcome roadblocks.




Job Requirements

Qualifications

Required:


  • Enrolled in Master’s Degree Program with emphasis in Data Science, Statistics, Economics, Math, Computer Science or other relevant fields. 
  • Experience in data science tools/techniques: R, Python, SPSS, data mining, etc or similar software.
  • Experience with relational databases and SQL
  • Experience with modeling structured and/or unstructured data, leveraging such techniques as penalized regression, multilevel modeling, ensemble models, or time series models
  • Experience with a variety of supervised and unsupervised machine learning methods