Data Scientist

at  Peraton

ABOUT PERATON

Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world’s leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees do the can’t be done by solving the most daunting challenges facing our customers. Visit peraton.com to learn how we’re keeping people around the world safe and secure.

Peraton seeks a Data Scientist to support DODIN inspections, assessments, evaluations, validations, Defensive Cyberspace Operations-Internal Defensive Measures (DCO-IDM) missions, self-assessments, and audit regimens.
Location: Fort Meade, MD.

Tasks include:

• Analyze and interpret industry standards, best practices, and metrics to develop reporting dashboards, risk management tooling to identify cyber risk trends, data analysis, and/or maturity opportunities.
• Develop predictive analytics models to forecast potential cybersecurity threats and risks.
• Collaborate to gather key stakeholder requirements and translate them into system use-case methodologies and technical specifications.
• Provide data analytics support and expertise in data science for specialized cybersecurity applications and big data analytical systems.
• Acquire, cleanse, and explore large datasets to identify patterns, trends, and insights, working with big data technologies and distributed computing platforms.
• Develop software programs, algorithms, and automated processes to cleanse, integrate and evaluate large cyber datasets from multiple disparate sources in a production environment.
• Use analytical rigor and statistical methods to analyze large amounts of data, extracting actionable insights using advanced statistical techniques such as data analysis, data mining, optimization tools and machine learning techniques and statistics.
• Manage development and deployment of predictive models based on historical data.
• Develop customer centric models and optimization tools to support large scale projects that use streaming and at-rest processing over structured and unstructured data.
• Develop and implement machine learning algorithms and models to solve complex business problems.
• Build predictive, prescriptive, or descriptive models in collaboration with stakeholders. Assess the performance of the predictive models and fine-tune them for accuracy.
• Create and utilize mathematical or statistical models to describe data characteristics, such as Confidence, Variability/Dispersion, distribution, quality.
• Plan and conduct complex analytical, mathematical, and statistical research that informs operational requirements. Write scripts using a variety of languages (e.g., R, Python, JavaScript, SQL, XQuery, jQuery, etc.) to process data as required.
• Design, develop, and modify software systems, using scientific analysis and mathematical models to predict and measure outcome and consequences of design.