Data Scientist TS SCI & VA Customer Favorable Poly Clearance

Required Experience

• 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.

• 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 visualizations tools such as Tableau, Kibana or Apache Superset.
• Demonstrated experience creating learning objectives and creating teaching curriculum in technical or scientific fields.