Data Scientist Associate

ConstructConnectAtlanta, GA
22hHybrid

About The Position

This position is hybrid in Peachtree Corners, Georgia and sits within our Product Development division, which develops, tests, and improves our software solutions in an innovative and collaborative environment. The Opportunity As Data Scientist Associate, you will work in a team to expand the analytics capabilities of the company by identifying business trends and solve complex problems. You will interpret results from petabytes of data using a variety of techniques, ranging from simple data aggregation via statistical analysis to complex data mining. You will also engage in developing Machine Learning and AI solutions to complicated problems on the leading edge of construction planning technology. You will have the opportunity to design, develop and implement best-in-class solutions for our organization and our clients.

Requirements

  • Bachelor’s Degree or equivalent experience in Statistics, Mathematics, Economics, Econometrics, Computer Science, or related quantitative discipline
  • Creative problem-solver who is passionate about digging into complex problems and devising new approaches to reach results.
  • Strong communication skills and experience distilling and presenting complex quantitative analysis into action-oriented recommendations.
  • Understanding of applied mathematics, statistics, and economics
  • Experience with a range of data science techniques including computer vision, NLP, and network analysis
  • Familiarity with Tensorflow or Pytorch
  • All team members must reside and perform their work within the United States

Responsibilities

  • Use data analysis combined with economic and business knowledge to make recommendations on the business direction to various stakeholders within the company.
  • Define and develop analytical, statistical and machine learning algorithms for advanced analysis and prediction
  • Work with Python and other technologies to do rapid design, prototyping, analysis, simulation, and experimentation.
  • Build massively scalable solutions and predictive models
  • Collaborate across the organization to develop curated training data sets for Machine Learning
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