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Captivation

Software engineering for mission-focused teams

Data Scientist 3 - MLOps

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeAnnapolis Junction, MD, USA$130k - $270k /yrIn-person

About the Job

Requirements

  • A minimum of ten years of experience in two or more of the following: designing or 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.
  • A bachelor's degree or higher from an accredited college or university in a quantitative discipline, such as statistics, mathematics, operations research, engineering, or computer science. Four additional years of experience in software development, cloud development, dataset analysis, or development of descriptive, predictive, and prescriptive analytics may substitute for a bachelor's degree.
  • A master's degree in a quantitative discipline may substitute for two years of experience, for a total of eight years of experience required.
  • A doctoral degree in a quantitative discipline may substitute for four years of experience, for a total of six years of experience required.
  • Must currently hold a Top Secret/SCI U.S. Government security clearance with a favorable polygraph; candidates must be U.S. citizens.

Responsibilities

  • Produce data visualizations that provide insight into dataset structure and meaning.
  • Work with subject matter experts to identify important information in raw data and develop scripts that extract this information from data formats such as SQL tables, structured metadata, and network logs.
  • Incorporate subject matter expert input into feature vectors suitable for analytic development and testing.
  • Translate customer qualitative analysis processes and goals into quantitative formulations 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 analytics performance using standard techniques and metrics such as cross-validation, ROC curves, and confusion matrices.
  • Oversee individual analytic efforts and guide the team in the analytic development process.
  • Guide analytic development toward solutions that 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 developing multiple analytic efforts.
  • Work with customers and subject matter experts to define analytic requirements and guide the team in formulating analytics that meet those requirements.
  • Guide the transition of prototyped analytics to production systems.
  • 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.

About the Company

Captivation

Software engineering for mission-focused teams

Captivation builds digital software for mission makers by delivering engineering services across a wide range of disciplines. The work is collaborative, with teams that move quickly like a small business and take pride in what they develop. The company emphasizes transparency, a flat organizational structure, and a developer-focused culture, which enables engineers to work directly and iteratively with clients. Compared with larger firms, Captivation differentiates itself through its focus on timely delivery, practical problem solving, and actively pursuing challenging projects for the Intelligence Community, using modern software technologies. The goal is to produce solutions that clients value, on time, while growing the team and empowering its engineers to take ownership of their work.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Columbia, MD
Founded
2014

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