Data Scientist in Fort Mill, South Carolina at AccruePartners

Date Posted: 11/30/2019

Job Snapshot

Job Description

THE TEAM YOU WILL BE JOINING:

  • Leader in the automotive and aerospace industry with the manufacturing of OEM and Industrial OEM
  • Technology focused organization who is on the cutting edge of manufacturing automation/digitization
  • North American Division near $2.5bil with a much larger global footprint

WHAT THEY OFFER:

  • Team leadership is very open to new ideas including tool/technology selection
  • This is a dispersed team, but a very cohesive unit
  • North American Leadership team is tenured and pushes for their employees to have the best possible work environment

WHERE THIS POSITION IS LOCATED:

  • Fort Mill, SC

WHAT YOU WILL DO:

  • perform exploratory data analysis, generate and test hypotheses, and uncover interesting trends and relationships
  • Prepare large data volumes, data mining and model building, creation of system prediction and system optimization models
  • Model structured data and implement algorithms to support analysis using advanced statistical and mathematical methods from statistics, data mining, econometrics, and operations research
  • Perform advanced analytics techniques to mine unstructured data, using methods such as document clustering, topic analysis, named entity recognition, and document classification

QUALIFICATIONS:

  • Bachelor’s or Master’s Degree in Computer Science, Business Information Systems Management, Mathematics or related field
  • Strong quantitative analysis background and experience in working with large, complex data systems to aggregate, organize, and prepare data for use in business analysis
  • Excellent understanding of complex data-based systems comprising relational and non-relational data
  • Deep experience in extracting, cleaning, preparing and modeling data
  • Strong knowledge in at least one of the following fields: statistics, data mining, statistics, operations research, econometrics, and/or information retrieval (machine learning and natural language processing is a plus)
  • Data visualization and/or power point presentation skills to effectively communicate insights is a plus
  • Proficiency in analysis (i.e. R, Python) packages
  • Knowledge of structural equation modeling, machine learning/AI and domain-specific languages (e.g. DSL)