Data Scientist, Senior/Level 3

Arcfield•Chantilly, 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