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Data Scientist III

Reflexive Concepts

  • Annapolis Junction, Maryland
  • 6 days ago

    Highlights

    The Data Scientist will develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense of datasets; prototype or consider several algorithms and decide upon final model based on suitable performance metrics; build models or develop experiments to generate data when training or example datasets are unavailable; generate reports and visualizations that summarize datasets and provide data-driven insights to customers; partner with subject matter experts to translate manual data analysis into automated analytics; implement prototype algorithms within production frameworks for integration into analyst workflows. A minimum of ten (10) years of experience in two (2) or more of the following: designing/implementing machine learning, data mining, advanced analytical algorithms, advanced statistical analysis, artificial intelligence, or software engineering with data analysis software such as R, Python, SAS, or MATLAB.

    Numbers & Facts

    LocationAnnapolis Junction, Maryland
    Websitehttp://www.reflexiveconcepts.com

    Description

    Reflexive Concepts is seeking a skilled Data Scientist III to join our growing team! 

    The Data Scientist will develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense of datasets; prototype or consider several algorithms and decide upon final model based on suitable performance metrics; build models or develop experiments to generate data when training or example datasets are unavailable; generate reports and visualizations that summarize datasets and provide data-driven insights to customers; partner with subject matter experts to translate manual data analysis into automated analytics; implement prototype algorithms within production frameworks for integration into analyst workflows.

    Qualifications:
    • Bachelor's degree or higher from an accredited college or university in a quantitative discipline (e.g., statistics, mathematics, operations research, engineering or computer science).
      • An additional four (4) years of experience in software development, cloud development, analyzing datasets, or developing descriptive, predictive, and prescriptive analytics can be substituted for a Bachelor's degree.
      • A Master’s Degree from an accredited college or university in a quantitative discipline can be substituted for two (2) years of experience for a total of eight (8) years of experience required.
      • A Doctoral Degree from an accredited college or university in a quantitative discipline can be substituted for four (4) years of experience for a total of six (6) years of experience required.
    • A minimum of ten (10) years of experience in two (2) or more of the following: designing/implementing machine learning, data mining, advanced analytical algorithms, advanced statistical analysis, artificial intelligence, or software engineering with data analysis software such as R, Python, SAS, or MATLAB.
    Required:
    • Significant MLOPS and Data Science background
    • Produce data visualizations that provide insight into dataset structure and meaning
    • Work with subject matter experts (SMEs) to identify important information in raw data and develop scripts that extract this information from a variety of data formats (e.g., SQL tables, structured metadata, network logs)
    • Incorporate SME input into feature vectors suitable for analytic development and testing
    • Translate customer qualitative analysis process and goals into quantitative formulations that are coded into software prototypes
    • Develop and implement statistical, machine learning, and heuristic techniques to create descriptive, predictive, and prescriptive analytics
    • Develop statistical tests to make data-driven recommendations and decisions
    • Develop experiments to collect data or models to simulate data when required data are unavailable
    • Develop feature vectors for input into machine learning algorithms
    • Identify the most appropriate algorithm for a given dataset and tune input and model parameters
    • Evaluate and validate the performance of analytics using standard techniques and metrics (e.g. cross validation, ROC curves, confusion matrices)
    • Oversee the development of individual analytic efforts and guide team in analytic development process
    • Guide analytic development toward solutions that can scale to large datasets
    • Partner with software engineers and cloud developers to develop production analytics
    • Develop and train machine learning systems based on statistical analysis of data characteristics to support mission automation
    • Lead a team of data scientists in the development of multiple analytic efforts
    • Work with customers and SMEs to define analytic requirements and guide the team in formulating analytics that meet requirements
    • Guide the transition of prototyped analytics to production system
    • Understand emerging machine learning and pattern recognition algorithms and guide a team of data scientists in integrating state-of-the-art algorithms into solutions
    • Delegate analysis responsibilities to one or more team members and monitor performance

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