Cybersecurity Solutions Architect/Engineer

Cybersecurity Solutions Architect/Engineer

Key Responsibilities: Applies expert level AI/ML analytic approaches to large volume of data from disparate sources to uncover cybersecurity threats and fraud schemes against the organization. Leverage Databricks to develop analytic solutions using Python, SQL, and R to create, interpret, visualize, and report on complex data to stakeholders at all levels. Responds to ad hoc requests from stakeholders to investigate concerns. Responsible for working across business units to identify, collect, aggregate, analyze new data sources, and advance the team's mission and reduce the time needed to deliver analytical insights. Responsible for highlighting and analyzing gaps in US Government Client systems and processes, as well as recommending remediation solutions to more effectively deter cybersecurity threats and fraudulent activity.

Required skills:
• Applicant must be an expert with data science and AI/ML concepts used for fraud detection. Demonstrated expertise in AI/ML solution development, data science practice, data strategy and governance, and customer and stakeholder engagement – all developed over many years of client work delivering solutions.
• Ability to design AI-powered solutions, integrating large language models, computer vision, and advanced analytics into secure, high-performing environments
• Ability to direct specialized teams comprising of data scientists, data engineers, and business intelligence specialists driving key AI and advanced technology solutions across secure environments.
• Manages delivery across multiple engagements including business intelligence, technology and tradecraft, financial operations, workforce analytics, cyber, artificial intelligence, risk management, and product development to enhance organizational performance (Python, SQL, Tableau, AWS).
• Advanced skills applying AI/ML tools to accelerate business activities including but not limited to programming and script development.

Expert level knowledge of:
• AI/ML Solution Architecture
• Data Science and Advanced Analytics
• Technology Strategy and Implementation
• Data Strategy and Governance
• MLOps and Model Lifecycle Management
• Azure Databricks
• Python, SQL, R Development

Experience:
• A minimum of eight (8) years' relevant experience.
• A degree from an accredited College/University in the applicable field of services is required. If the individual's degree is not in the applicable field then four additional years of related experience is required.