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Department Summary:
MITRE's Law Enforcement (LE) and U.S. Coast Guard Department focuses on operational support across a broad range of mission outcome areas for Homeland Security sponsors. The LE & USCG Department strives to provide excellence in systems engineering, operational modeling, cybersecurity, intelligence analysis, AI/ML data analytics, sensor systems, and terrestrial & satellite communications with an emphasis on both analytical and lab-based experimentation.
MITRE is seeking an experienced Senior Data Scientist who will lead high-visibility/high-impact efforts that provide significant contributions to the safety and security of the United States. The position will work closely with sponsor staff and regularly engage with senior leaders to understand their priorities and shape work, and they will be a strong collaborator across the Division and MITRE Public Sector (MPS). Major focus areas include criminal network analysis and disruption, digital marketplaces, and transnational criminal organizations and associated activities. Additional areas of responsibility include cybercrime investigation improvement, cyber-mission systems engineering and guidance, system-of-system engineering, data engineering and analysis, experimentation, communications, and acquisition.
Roles and Responsibilities:
In this role, the selected candidate will provide strategic and operational leadership as a trusted advisor to senior leaders within the sponsor's organization in the areas of analysis and tradecraft in the fight against crime. Further, the selected candidate will contribute to efforts to:
Develop and implement advanced data models to identify cyber threats, utilizing extensive data sources to analyze adversarial behavior patterns, including Dark Web activity and cryptocurrency transactions.
Analyze structured and unstructured datasets from diverse sources, integrating insights about threat actors, malware campaigns, and financial movements across underground digital markets.
Lead the development of Python-based analytical tools to enhance the collection, transformation, and analysis of complex datasets, optimizing workflows for threat intelligence operations.
Serve as the go-to problem solver for challenging issues related to cyber intelligence, with colleagues and team members regularly seeking your expertise to address and resolve hard-to-crack problems.
Perform deep dives into emerging cyber threats, focusing on areas such as blockchain analysis, cryptocurrency tracing, and Dark Web intelligence, providing actionable insights that enhance defensive measures.
Design, implement, and maintain scalable data infrastructure that supports rapid data analysis and enables advanced querying and data mining in support of cyber threat intelligence objectives.
Collaborate with cross-functional teams, including threat analysts, software engineers, and cybersecurity experts, to understand mission requirements, translate them into data science solutions, and deliver timely results.
Communicate complex findings effectively through reports, dashboards, and presentations tailored for both technical and non-technical audiences, supporting strategic decision-making and operations planning.
Basic Qualifications:
Typically requires a minimum of 5 years of related experience with a Bachelor's degree in Data Science, Computer Science, Cybersecurity, or related field; or 3 years and a Master's degree; or a PhD with relevant experience who can immediately contribute at this job step; or equivalent combination of related education and work experience.
Relevant prior military and/or law enforcement experience can be accepted in place of formal education and/or experience requirements.
Demonstrated expertise in Python with hands-on experience using data science libraries like Pandas, NumPy, and Scikit-learn for data analysis and machine learning.
Proven experience working with large-scale data stores, such as SQL databases, NoSQL (e.g., MongoDB), graph databases (e.g., Neo4J), or big data frameworks (e.g., Hadoop, Spark).
Solid understanding of cyber threat intelligence concepts, including adversary tactics, techniques, and procedures (TTPs), threat vectors, and actor behaviors.
Knowledge of blockchain technologies, cryptocurrency trends, and underground digital markets, with the ability to analyze blockchain transactions and the flow of cryptocurrency in the context of cyber threats.
Demonstrated ability to tackle complex problems and develop innovative solutions, showing persistence and resourcefulness in ambiguous situations.
Strong communication skills, with experience in developing clear, actionable reports and visualizations (e.g., Matplotlib, Plotly, Tableau) for diverse audiences.
Ability to obtain and maintain a TS/SCI clearance within the first year of service.
This position requires full-time on-site presence with the sponsor in Houston, TX.
Willingness to travel (up to ~20%).
Preferred Qualifications:
Master's degree in Data Science, Cybersecurity, or related field with specialization in areas such as cryptocurrency analysis, blockchain forensics, or Dark Web intelligence.
Experience conducting research and analysis on the Dark Web, deep web, and other underground online environments, leveraging data to identify threats.
Experience with trusted AI or explainable AI techniques applied to cybersecurity and intelligence problems.
Working knowledge of cloud environments (e.g., AWS, Azure) and MLOps, with a focus on deploying scalable analytics solutions.
Previous work experience in a classified environment, actively participating in cyber threat modeling, operational intelligence, or incident response.
Previous work experience performing (or providing data science support to) targeting analysis for HUMINT, cyber, and/or kinetic operations.
Active Top Secret or TS/SCI clearance is strongly preferred.
This requisition requires the candidate to have a minimum of the following clearance(s):
None
This requisition requires the hired candidate to have or obtain, within one year from the date of hire, the following clearance(s):
Top Secret/SCI
Work Location Type:
Onsite
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