Data Scientist - TS/SCI w/Poly

The Sponsor provides training, tradecraft guidance and tools for the data science workforce that improve the reuse of successful data science methods. The Sponsor’s office completes short-term prioritized data science projects, which require programmatic and technical support. The work is performed within a team environment and requires constant iteration with stakeholders to provide services and tools. Work will include development and maintenance of training, publication and coordination of tradecraft guidelines and services as well as development of programming packages and data services to support cross-enterprise needs. Work will include high technical skill in programming as well as high levels of collaboration, communication and requirements solicitation.

Location: McLean, VA

Demonstrated experience with data engineering, to include designing and building data infrastructure, developing data pipelines, transforming/preparing data, ensuring data quality and security, and monitoring/optimizing systems.

Demonstrated experience with data management and integration, including designing and operating robust data layers for application development across local and cloud or web data sources. Demonstrated work experience programming with Python

Demonstrated experience building scalable ETL and ELT workflows for reporting and analytics.

Demonstrated experience with general Linux computing and advanced bash scripting Demonstrated experience with SQL.

Demonstrated experience constructing complex multi- data source queries with database technologies such as PostgreSQL, MySQL, Neo4J or RDS

Demonstrated experience processing data sources containing structured or unstructured data

Demonstrated experience developing data pipelines with NiFi to bring data into a central environment

Demonstrated experience delivering results to stakeholders through written documentation and oral briefings

Demonstrated experience using code repositories such as Git

Demonstrated experience using Elastic and Kibana technologies Demonstrated experience working with multiple stakeholders

Demonstrated experience documenting such artifacts as code, Python packages and methodologies

Demonstrated experience using Jupyter Notebooks Demonstrated experience with machine learning techniques including natural language processing

Demonstrated experience explaining complex technical issues to more junior data scientists, in graphical, verbal, or written formats

Demonstrated experience developing tested, reusable and reproducible work Work or educational background in one or more of the following areas: mathematics, statistics, hard sciences (e.g. Physics, Computational Biology, Astronomy, Neuroscience, etc.) computer science, data science, or business analytics Desired Skills and

Desired:

Demonstrated experience with cloud services, such as AWS, as well as cloud data technologies and architecture.

Demonstrated experience using big data processing tools such as Apache Spark or Trino

Demonstrated experience with machine learning algorithms

Demonstrated experience with using container frameworks such as Docker or Kubernetes

Demonstrated experience with using data visualization tools such as Tableau, Kibana or Apache Superset

Demonstrated experience creating learning objectives and creating teaching curriculum in technical or scientific fields