Data Scientist, Senior/Level 3

ArcfieldChantilly, VA
73d

About The Position

Arcfield's Cyber programs are expanding and currently in need of Data Scientist, Senior/Level 3 professionals providing data management and analysis to assist in recommending changes to the Government that can improve operational effectiveness and support decision making. Note: An offer for this position is contingent upon contract award.

Requirements

  • Must possess and maintain a TS/SCI clearance with Poly
  • BS 10-12, MS 8-10, PhD 5-7
  • 7 years of experience in data science, mathematics, statistics, business analytics, or equivalent quantitative field
  • Demonstrate ability to prepare and analyze data visualizations
  • Demonstrate ability to select appropriate analytical approaches towards automation
  • Demonstrate ability to review and refine requirements for data science cybersecurity approaches
  • Demonstrate strong understanding of Large Language Models (LLMs)
  • Demonstrate strong understanding of machine learning principles, techniques, and technologies
  • Demonstrate strong knowledge of data engineering
  • Demonstrate strong knowledge of data management
  • Familiar with Agile processes (Scrum, Jira, Confluence)
  • Strong working experience with numerous projects on the following or equivalent: AWS Spark Kafka Tableau Python (e.g. TensorFlow and PyTorch) R (e.g. tidyverse, Rshiny) Splunk
  • Familiarity with Agile or equivalent project management process

Nice To Haves

  • Exposure to cybersecurity applications or operations
  • A STEM degree in data science, mathematics, statistics, business analytics, or equivalent quantitative field
  • Experience with various software development stacks, data transport and transformation APIs, and technologies
  • Ability to utilize cloud-based data analysis tools, visual analytic tools, and open-source textual processing technologies
  • Experience with software development stacks, data transport and transformation APIs, and technologies
  • Demonstrated experience working on complex technical problems and provide innovative solutions
  • Ability to deliver recommendations for business and analytic decisions based on data insights

Responsibilities

  • Extract, transform, load, analyze, and interpret relevant information assurance (IA) data for timely analytic use
  • Provide reports on associated patterns, anomalies, and potential security concerns
  • Analyze historical data to gain insights, understand patterns, anomalies, and potential security considerations, and present findings clearly and concisely
  • Conduct predictive analytics to prepare models and algorithms for identifying, characterizing, and forecasting future outcomes
  • Perform prescriptive analytics to recommend optimal actions
  • Integrate analytic findings and outcomes into other cybersecurity products and processes, including Continuous Monitoring
  • Conduct ongoing research on emerging data science methodologies and technologies, providing reports and recommendations for adoption
  • Assist in creating, editing, managing, and archiving information within data sources
  • Ensure accuracy of datasets and records
  • Support relevant data management activities
  • Work on complex technical problems and provide innovative solutions
  • Analyze unstructured and semi-structured data using advanced techniques such as latent semantic indexing (LSI), entity identification and tagging, and complex event processing (CEP)
  • Apply analysis algorithms on distributed, clustered, and cloud-based high-performance infrastructures
  • Handle processing and index requests for high-volume data collections and high-velocity data streams
  • Develop and deploy sophisticated applications using advanced unstructured and semi-structured data analysis techniques
  • Utilize advanced tools and computational skills to interpret, connect, predict, and make discoveries in complex data
  • Deliver recommendations for business and analytic decisions based on data insights
  • Work with various software development stacks, data transport and transformation APIs, and technologies
  • Utilize cloud-based data analysis tools, visual analytic tools, and open-source textual processing technologies
  • Apply machine learning, algorithm analysis, and data clustering techniques in data science projects
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