Senior Data Scientist Spectral with Security Clearance

Job Description
Senior Data Scientist Spectral Position Requirement:
• MUST BE A US CITIZEN
• ACTIVE TS/SCI CLEARANCE REQUIRED
• MUST HAVE 8-10 YEARS OF EXPERIENCE AS A DATA SCIENTIST WITH PERFORMING THIS ROLE AT THE NATIONAL GEOSPATIAL INTELLIGENCE AGENCY or ANOTHER INTEL AGENCY REQUIRED Locations: Springfield, VA
Job Type: Full-Time Employee Overview: Successful candidate must have demonstrated experience Geospatial Intelligence Analysis to develop, test and validate operational prototypes and algorithms and methods to improve imagery and geospatial science and imagery analysis tradecraft. Duties:
• Domain knowledge / intelligence community (IC) Background in intelligence, defense, international relations, or public administration in multi-disciplines. Demonstrated familiarity with US intelligence community specific GEOINT collection and exploitation. Experience collaborating with all national and service intelligence agencies/centers. Demonstrated familiarity with GEOINT community and associated TPED products.
• Proficient in Python, PIG, Java, Javascript, SQL, R, spatial analysis tools and concept, data mining methods, database structures, analytical information extraction and visualization, training in applied math including statistics, math modeling to support temporal and pattern analysis, correlation of events, probability analysis, assessment of sampling, ANOVA and error, regression testing and analysis, hypothesis testing, visualization, process automation, familiarization with modeling software (JEMA, Hyperion, Breakdown, FME, SPSS, SAS for process repeatability, efficiency, knowledge capture, hypothesis testing, visualization, process automation. Experience with managing data science projects, workflows, programmatically connecting database and web data sources, knowledge and skills in data mining, cleansing, exploring spatial/non-spatial and temporal data both in structured and non-structured formats, experience with two or more cloud tools (Data Bricks, Docker containers, Jupyter Hub, Zeppelin, Apache Spark, Centos, Jenkins, GIT), and experience with ESRI tools and software.
• Utilize advanced analytic tools and techniques to analyze data and help analysis to improve performance and decision making.
• Derive data insights for analysis by using complex ML and visualization techniques
• Automate existing, and improve efficiencies of, analytic workflows through Analysis Directorate.
• Develop scripts to pull data from ESRI database, CTD and NGA and NGA mission partner' databases.
• Optimize existing databases to speed query, I/O, visualization of data, and coordinate with LOB's analytic modernization team to develop and document strategies to expose new datasets and create migration plans for legacy systems.
• Develop and progress AI and ML and CV workflows to improve efficiency of GEOINT analysis.
• Build and develop custom solutions (tools, processes, etc.) that adhere to enterprise architecture standards to automate and assist analytic endeavors as submitted by LOB's analytic units.
• Facilitate Mind Map sessions to deconstruct intelligence problems, discover new KIQ's and create schema to maximize analyst's workflow and support effective time management.
• Establish analytic rigor, maintain trust in NGA GEOINT assessments by creating data commonality in criteria, and core principles and language.
• Support database requirements for data visualizations, collection models and performance analytics that enhance analyst workflows.
• Visualize SOM, CTD activity, structured and unstructured data using reporting tools approved by NGA while automating data flow to report system.
• Assist development of data schemas compatible with international partners for interoperability.
• Document effective communication work performed, results, and associated impact in writing weekly or as required to inform formal intelligence reports, office activity reports, and facilitate knowledge management and broad sharing of information. Required Skills and Experience:
• Ph.D. in quantitative discipline such as data mining, statistics, earth science, geographic information science, computer science, physics, or a related field.
• Computational analytic modeling
• Experience in engineering and tuning deep learning algorithms for data science
• Experience with two or more (2+) languages (e.g. Python, PIG, Java, Javascript, SQL, R)
• Experience running command-line operations in one or more (1+) operating systems (e.g. Windows, Linux)
• Experience with two or more (2+)visualization tools packages (e.g. GGPLOT, PLOTLY, MATPLOTLIB, D3, TABLEAU, BOKEH)
• Experience connecting two or more (2+) databases (e.g. Postgres, Oracle, SQLlite, ArcSDE) and web data sources (e.g. API's, GeoJson, REST).
• Demonstrated developer experience with two or more (2+) cloud-based technologies (e.g. Docker containers, Jupyter Hub, Zepplin, Apache-Spark, Centos, Jenkins, GIT).
• Domain knowledge / intelligence community (IC) Background in intelligence, defense, international relations, or public administration in multi-disciplines. Demonstrated familiarity with US intelligence community specific GEOINT collection and exploitation. Experience collaborating with all national and service intelligence agencies/centers. Demonstrated familiarity with GEOINT community and associated TPED products. OR
• Master of Science (MS) degree or higher, in a quantitative discipline such as data science, mathematics, statistics, earth sciences, quantitative social science, geographic information science, computer science, physics, or related field. In conjunction with proficiency and at least 7-year's experience with applied data processing and scientific analysis of large datasets and machine learning (ML).
OR
• Bachelor of Science in quantitative discipline such as above, and Extensive knowledge of programming languages (e.g. Python, PIG, Java, SQL, R), spatial analysis tools and concepts, data mining methods, database structures and analytic information extraction and visualization Training in applied mathematics, including statistics and mathematics modeling to support temporal and pattern analysis, correlation of events, probability analysis, assessment of sampling, analysis of variance error, regression testing, analysis demonstrated competency in one or more knowledge capture, hypothesis testing, visualization, and process automation. Familiarization with modeling software (e.g. FMS, SPSS, SAS) for process repeatability, efficiency, knowledge capture, hypothesis testing, and process automation. Demonstrated experience relevant to managing data science projects and workflows Demonstrated experience programmatically connecting to database and web-based data sources and non-spatial data in both structured and non-structured formats. Demonstrated knowledge and experience in data mining, cleansing, and exploring spatial, temporal, and non-spatial data in both structured and non-structured formats. Demonstrated developer experience with two or more (2+) cloud-based technologies (e.g. Docker containers, Jupyter Hub, Zepplin, Apache-Spark, Centos, Jenkins, GIT). Proficiency in Microsoft Office