Data Scientist 3

Gormat

$100K — $140K *
Information Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's Degree with 10 years of relevant experience, or Associates degree with 12 years of relevant experience.
  • Degree must be in Mathematics, Statistics, Data Science or related fields with substantial computational coursework.
  • Experience in designing and implementing machine learning and advanced analytical algorithms.
  • Strong programming skills in Python and familiarity with data manipulation and automation.
  • Knowledge in statistical analysis and data management techniques.

Responsibilities

  • Leverage Python expertise to automate workflows and streamline data processes.
  • Create insightful data visualizations using Jupyter Notebooks for decision-making.
  • Develop strategies for extracting value from large datasets, focusing on mission-specific analytic questions.
  • Translate complex technical requirements into actionable insights for non-technical stakeholders.
  • Support critical systems for ONM, collaborating with policy decision makers if needed.

Benefits

  • Opportunity to work on critical data systems with significant national impact.
  • Potential collaboration with senior decision-makers and policy analysts.
  • Training and professional development opportunities in advanced data techniques.
Full Job Description
Job Description:

We are seeking a Data Scientist proficient in Python and experienced in automating workflows, data manipulation, and visualization using Jupyter Notebooks. This role involves leveraging Python expertise to streamline processes and create insightful visualizations for data-driven decision-making.

The Level 3 Data Scientist shall possess the following capabilities:
  • Foundations: (Mathematical, Computational, Statistical).
  • Data Processing: (Data management and curation, data description and visualization, workflow and reproducibility).
  • Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations).
  • Devise strategies for extracting meaning and value from large datasets. Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application specific knowledge. Through analytic modeling, statistical analysis, programming, and/or another appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique features and limitations inherent in DOD data holdings. Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others with drawing appropriate conclusions from the analysis of such data. Effectively communicate complex technical information to non-technical audiences. Make informed recommendations regarding competing technical solutions by maintaining awareness of the constantly shifting DOD collection, processing, storage and analytic capabilities and limitations.
  • Support to ONM for critical systems. Potential for collaboration with policy and decision markers. Familiarity with excel, SharePoint, python, and an ability to scope projects/provide use cases for workflow integration. Experience with metrics, dashboards, and data visualizations will be beneficial.

Qualifications:
  • Bachelor's Degree with 10 years of relevant experience.
  • Associates degree with 12 years of relevant experience.
  • Bachelor's Degree must be in Mathematics, Applied Mathematics Statistics, Applied Statistics, Machine learning, Data Science, Operations Research, or Computer Science or a degree in a related field (Computer Information Systems, Engineering), a degree in the physical/hard sciences (e.g. physics, chemistry, biology, astronomy), or other science disciplines with a substantial computational component (i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g. algorithms, programming, , data structures, data mining, artificial intelligence). College-level requirement, or upper-level math courses designated as elementary or basic do not count. Note: A broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university.
  • Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least one high-level language (e.g. Python)), statistical analysis (e.g. variability, sampling error, inference, hypothesis testing, EDA, application of linear models), data management (e.g. data cleaning and transformation), data mining, data modeling and assessment, artificial intelligence, and/or software engineering. Experience in more than one area is strongly preferred.

TS/SCI with polygraph is required.

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