SME Data Scientist - Poly clearance required!

at  Praxis Engineering

WHAT YOU WILL NEED

• Working knowledge appropriate analytic methods and methodological tools in one or more of the following areas:
• Applied mathematics (e.g. probability and statistics, formal modeling, computational social sciences)
• Computer programming (e.g. programming languages, math/statistics packages, computer science, machine learning, scientific computing)
• Visualization (e.g. GIS/geospatial analysis, telemetry analysis)
• Working knowledge of research designs
• Intellectual curiosity; creativity and innovation to go beyond current tools to deliver the best solutions to complex problems.
• Strong analytical and critical thinking skills
• Ability to leverage multiple data management tools to organize relevant information and make decisions
• Ability to develop comprehensive software applications, as needed
• Ability to translate complex, technical findings into an easily understood narrative
• Ability to work collaboratively and effectively in a team environment
• Technologies to know:
• Statistical Tools may include: SAS, R, SPSS, Matlab, Mahout/MADlib, Stata
• Technology Tools: AWS, Open Search and Python Data Science tools
• Programming languages: SQL, C/C++, JAVA, Python, Perl
• Data Management Tools my include: Hadoop tools, MapReduce, Pig, Hive, NoSql, Tableau, Hbase
  Qualifications: 8+ years of experience bachelor’s degree in quantitative or technical field of study (e.g., statistics, mathematics, computer science, physical science, quantitative social sciences)

The Expert-level Data Scientist will be working with established programmatic and quantitative methods to find patterns and relationships in large data sets; conducting mathematical, statistical or other data-driven problem-solving analysis to identify business operations or intelligence questions by internal and external customers. They are expected to work independently with minimal supervision by first line supervisor or government client.

• Independently compile data to address the most complex intelligence issues or problems for senior internal/external customers.
• With minimal supervision provide accurate, timely, complex and sophisticated data analysis in support of key Agency, US national security, and foreign policy objectives and to shape Intelligence Community (IC) analysis priorities.
• With minimal supervision, conceive, prepare, and communicate a wide range of strategic, highly complex graphics, computational models/tools, or written/oral assessments to internal and external customers (e.g., policymakers, IC components).
• Manage projects and associated resources.