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Data Architect

Centreville, Virginia
Permanent | Job ID #60682 | Posted Last Month

Data Architect is needed for a full time perm position with a client onsite in Virginia.


This is a challenging position for a mid- to senior-level, data-savvy professional on a new and exciting project, which has the real potential to be a game-changer in the Sponsors tool box of expert analytic systems.

This position is for a well-rounded data expert (including data architect, data scientist, data engineer, data analyst) who can enhance mission value by helping the team and customer exploit existing Artificial Intelligence / Machine Learning (AI/ML) prototypes by transforming them into production-ready algorithms in a new enterprise AI/ML platform, which will be architected and recommended by the team at large.

This person could be tasked to prepare and deliver both technical and high-level briefings on data-related matters that are relevant to the customer’s overall AI/ML strategy. including briefings with proposed changes to optimize project use of the data.

This person is expected to possess and deliver exceptionally strong technical and ETL skills, because the data-related functions are central to the project's overall success. The ETL tasks could require basic programming skills, because the data sets will need to be cleansed, segmented, normalized, reassembled, and exploited using a variety of extraction and visualization tools.
This person could also be expected to participate in the evaluation of new tools for the project, and those tools could range in type from extraction tools to highly sophisticated advanced analytic tools.
This person would be expected to possess a natural desire to keep abreast of the latest tools (open source, Sponsor's Proprietary (Equipment, Software), and COTS) for data science/data architecture so that he/she could work effectively with other incubating technologies and help the project identify better capabilities.


  • Holds a Bachelor's degree or equivalent in computer science, data science, data architecture, data analysis, or related field of study.
  • Minimum of two years of demonstrated experience as a data expert (data analyst, data scientist, data architect) with Sponsor or Sponsor's partners.
  • Demonstrated experience of developing analysis and advanced research products by incorporating varying data elements and by building on techniques and theories from many fields, including signal processing, mathematics, probability models, machine learning, statistical learning, computer programming, data engineering, pattern recognition and learning, visualization, uncertainty modeling, data warehousing, and high performance computing.
  • Demonstrated experience creating a data model that effectively integrates mission needs with underlying data structures.
  • Demonstrated experience interpreting rich data sources, merge data sources together, ensure consistency of data-sets, create visualizations to aid in understanding data, present and communicate the data insights/findings to specialists and scientists in their team and if required to a naive audience.
  • Demonstrated experience collaborating with non-technical audiences and/or analysts to extract meaning from data and to create data products.

Desired, but Optional Skills:

  • Master's degree or Ph.D in data science, data architecture, data analysis, or related field of study.
  • Demonstrated experience with designing, testing and deploying dashboards and/or other user interface (U/I) features for data scientists or analysts with this Sponsor or Sponsor's partners.
  • Demonstrated experience with developing a complete data taxonomy, ontology, or metadata standard from scratch as well as merging two data specifications from differing projects.
  • Demonstrated experience with Sponsor's or Sponsor's partners data architecture constructs, including metadata standards, PUBS-XML, NewsML, or comparable XML formats.
  • Demonstrated experience with 1010data Appliance, entity extraction tools (e.g. Aerotext), and/or Digital Reasoning Synthesis (DRS), or other similar advanced computing systems, such as those involving natural language processing or advanced analytics.
  • Demonstrated ability of using data science techniques to conduct research across various domains, including the political science, economics, social sciences and the humanities.
  • Demonstrated experience of working with conventional tools for Big Data and Data Science, such as Big Data manipulation tools (e.g. Hadoop, Pig, Hive, Python) or statistical analysis tools (e.g. SAS, SPSS, R), or data warehouse and loading tools (e.g. Teradata, Informatica).

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