Data Scientist - AI/ML (DCO)

What You'll Be Doing

• Perform/utilize statistics, machine learning, and analytic approaches to answer key intelligence questions, producing results and re-usable products that provide real value to Intelligence Analysts.
• Apply machine learning techniques to identify and transform data features, find hidden patterns and trends, build and optimize classifiers, create automated anomaly detection systems, and automate steps of a process.
• Evaluate statistical models to determine the validity of analyses, implement evaluated models into production by collaborating with software developers, periodically re-evaluate and refine machine learning models being used in production.
• Curate and collect data from a variety of traditional and non-traditional sources: extract data from sources, transform and integrate data in line with existing data, and load data into data stores for access by others.
• Collaborate with Data Scientists to develop processes and tools to monitor and analyze model performance and data accuracy.
• Work with analysts to interpret analytic results and refine analysis as needed.
• Effectively communicate results and ideas to key decision makers, analysts and other stakeholders and shall provide information as appropriate.
• Perform documentation of all processes, models and activities by developing, documenting, and implementing a configuration management plan for data sets.
• Research latest data science tradecraft and technology.

Required Skills

• Active TS SCI with polygraph required for consideration
• Bachelor's degree in relevant field and 8 years of experience; an advanced degree will be considered in lieu of years of experience
• Three or more years of Defensive Cyber Operations experience
• Three or more years of Machine Learning techniques and statistical model evaluation

Desired Skills

• Master's degree in relevant field and 4 years of experience
• Demonstrated proficiency with R or Python and SQL to manipulate data and draw insights from large and small data sets
• Exposure to AWS (Amazon Web Services), Cisco CCNA, STIGs IAVA, Big Data Platform (BDP)
• Strong background and skills in Linux Ubuntu CentOS RHEL, Windows, and virtual environments
• A problem solver who can get in, be given a project, and use engineering skills to determine a solution