Data Scientist 3

Gormat

$110K — $140K *
Information Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's Degree in relevant fields with 10 years experience or an Associate's Degree with 12 years of related experience.
  • Degree must include substantial coursework in advanced Mathematics or Computer Science.
  • Broader degrees considered with a Data Science Certificate from an accredited institution.
  • Experience in machine learning, data analysis, and statistical methodologies is essential.
  • Proficiency in at least one high-level programming language (e.g., Python) is necessary.
  • Previous engagement in data management, cleaning, and transformation is required.

Responsibilities

  • Support an NLP project by tokenizing language data automatically.
  • Develop automated annotation solutions for parts of speech in language data.
  • Enhance existing models by evaluating performance against human-generated annotations.
  • Translate mission needs into technical requirements for data analysis.
  • Communicate complex analysis results to non-technical stakeholders.
  • Conduct statistical analysis and modeling of large datasets for insights.

Benefits

  • Opportunity to work on cutting-edge NLP technology.
  • Exposure to advanced data science methodologies.
  • Collaboration in a mission-focused environment.
  • Professional growth and development opportunities.
Full Job Description
We are seeking a Data Scientist proficient in Python and Jupyter Notebook to support a Natural Language Processing (NLP) project. You will help to accurately and automatically tokenize language data with spoken or written origins, develop automated solutions for the annotation of language data with parts of speech information, and improve existing models by scoring performance against human-generated annotations for speech and text.

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).
  • Ability to make and communicate principal conclusions from data using elements of mathematics, statistics, computer science, and applications-specific knowledge.
  • Ability to use 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 feature and limitations inherent in Government 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.
  • DS position in X32 as a support for a Natural Language Processing (NLP) project to accurately and automatically tokenize language data with spoken or written origins; develop automated solutions for the annotation of language data with parts of speech information, and improved existing models by scoring performance against human-generated annotations for speech and text.

Qualifications:
  • Bachelor's Degree with 10 years of relevant experience, associate's degree with 12 years of experience may be considered for individuals with in-depth experience that is clearly related to the position.
  • 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.
  • 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 on 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.

TS/SCI with polygraph is required.

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