Quick overview
Job description
Role Title: Senior Data Scientist Clearance: Public Trust (candidate does not need current public trust clearance but must be eligible) Location: Hybrid/Washington DC (estimated 1-3 days onsite per week) Education: A bachelor’s degree is required, or equivalent experience and education; data-science education is desirable.
Required Skills
4+ years of experience in custom AI training (to include supervised and unsupervised) and Natural Language Processing (NLP) expertise focusing on unstructured data;
5+ years of in-depth knowledge of at least one analytical/statistical language (Closure, Scala, Python, R);
2+ years of experience manipulating unstructured data from different platforms;
2+ years of experience with data visualization tools such as Elastic X-Pack (including Graph), Power BI, Tableau, or Qlik.
Day-to-day Responsibilities
The Senior Data Scientist works with [client] stakeholders to clarify analytical needs, identify suitable data sources, and translate mission questions into practical analyses or models. Day to day, this includes exploring and assessing data, preparing it for analysis, and using SQL, Python, and statistical or machine-learning methods to identify patterns, gaps, and potential insights.
The role builds, tests, and refines analytical workflows in the AWS GovCloud environment, using services such as Amazon S3, AWS Lambda, Amazon EC2 or Fargate, and managed database or analytics services as appropriate. Responsibilities may include preparing datasets, developing and validating models, and integrating work with existing data pipelines and platforms. The Senior Data Scientist documents methods, assumptions, results, and model limitations so work is reproducible and auditable.
They also participate in project meetings and reviews, communicate risks and trade-offs, and recommend practical improvements to performance, reliability, or maintainability.
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