Data Scientist - AI/ML (TS/SCI w/ Poly)

1w1 week ago

Parsons Corporation

US · Full-time · $112,200 – $196,400

About this role

Parsons seeks an experienced Data Scientist for embedded Defensive Cyber operations support, capability integration, and rapid prototyping in support of USCYBERCOM. Collaborate with headquarters and local customers to develop analytic capabilities. Serve as a critical team member applying high-level software engineering to national security missions.

Utilize statistics, machine learning, and analytic approaches to answer key intelligence questions and produce reusable products for analysts. Apply techniques to transform data features, detect anomalies, and automate processes. Evaluate models, implement into production, and refine them periodically.

Curate data from traditional and non-traditional sources, integrating it for access by others. Work closely with analysts and Data Scientists on a small team to monitor performance and interpret results. Communicate findings effectively to decision makers and stakeholders.

Join an innovative culture valuing people, agility, and growth on the Federal Solutions team. Research latest data science tradecraft and technology. Document processes, models, and activities with configuration management plans.

Requirements

Active TS/SCI w/ polygraph required
Bachelor's degree in relevant field and 8 years of experience; advanced degree considered in lieu of experience
3+ years of Defensive Cyber Operations experience
3+ years of Machine Learning techniques and statistical model evaluation
Master's degree in relevant field and 4 years of experience (desired)
Proficiency with R or Python, and SQL to manipulate data and draw insights
Exposure to AWS, Cisco (CCNA), STIGs/IAVA, Big Data Platform (BDP)
Strong background in Linux (Ubuntu, CentOS, RHEL)/Windows/Virtual environments

Responsibilities

Perform statistics, machine learning, and analytic approaches to answer key intelligence questions and produce reusable products
Apply machine learning techniques to identify data features, find patterns, build classifiers, create anomaly detection systems, and automate processes
Evaluate statistical models for validity, implement into production with developers, and re-evaluate models in production
Curate and collect data from traditional and non-traditional sources, transform, integrate, and load into data stores
Collaborate with Data Scientists to develop processes and tools to monitor model performance and data accuracy
Work with analysts to interpret analytic results and refine analysis as needed
Communicate results and ideas to key decision makers, analysts, and stakeholders
Document processes, models, and activities; develop and implement configuration management plans for data sets; research latest data science tradecraft