Data Scientist Analyst

PlanIT Group
Job LocationUS
Job TagUS Full-Time Jobs


Location: Fort Bragg, NC

Basic Skills:

  • Perform exploratory research and analysis to identify novel and meaningful patterns in data and uses statistical methods to reject or accept proposed hypotheses about relationships or latent predictive factors discovered through their work to provide business value.
  • Uses a combination of tools, technologies, and numerical computing systems (i.e.: GPU processing, distributed computing, highly parallel coding, cloud computing, machine learning, visualization, system modelling and simulation) to achieve results.

Areas of expertise should include several of the following:

  • Applied statistics, text mining, natural language processing, deep learning, optimization, and other similar fields.
  • Work on datasets with applied statistics and machine learning algorithms;
  • Use exploratory data analysis techniques to identify meaningful relationships, patterns, or trends from complex data sets and discover opportunities in datasets to support decision-making;
  • Develop predictive models and new algorithms to solve data / business problems;
  • Understand the math and statistics behind the models and interpret, extrapolate, and prescribe from data to deliver actionable recommendations using effective visualizations.

Specific Tasks:

  • Perform exploratory data analysis (EDA) to determine how to handle missing data and to look for trends and/or opportunities.
  • Solving business problems through undirected research and framing open-ended enterprise questions.
  • Employ sophisticated analytical methods, machine learning and statistical methods to prepare data for use in predictive and prescriptive modeling.
  • Extract immense volumes of structured and unstructured data.
  • Query structured data from relational databases using programming languages such as SQL
  • Gather unstructured data through web scraping, APIs, and surveys
  • Perform exploratory research and analysis to identify novel and meaningful patterns in data
  • Thoroughly clean data to discard irrelevant information and prepare the data for preprocessing and modeling.
  • Discovering new algorithms to solve problems and build programs to automate repetitive work
  • Recommend cost-effective changes to existing procedures and strategies.
  • Analyze, process, and model data then interpret the results to create actionable plans for the enterprise and other organizations.”

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