Data Scientist designing, developing, and implementing data science solutions to empower investigators. Collaborating with SMEs and vendors to enhance capabilities in extracting valuable information.
Responsibilities
Collaborate with subject matter experts, team leads, and third-party vendors to define new features and functions for automation, aiding investigators in extracting meaningful information about a target and their surrounding network.
Design, code, test, and document data science microservices primarily in Python.
Support the integration of disparate bulk data sources into a unified database.
Develop and optimize graph traversal queries and analytic pipelines to support analyst use cases, ensuring smooth transition from development to test and production environments.
Extract valuable information from unstructured text, including SAR narratives and web scraped data related to cryptocurrency addresses and actors.
Generate synthetic data for testing and development environments, as well as for the MM capstone training, adapting to evolving MM training and data holdings.
Requirements
Proficient in Python programming.
Experience with graph traversal languages such as Gremlin, Cypher, or GraphML, along with expertise in network analytics, including centrality, community detection, link prediction, pattern recognition, and/or blockchain analytics.
Strong SQL or other relational database query experience.
In-depth knowledge of graph-structured data and analytics.
Knowledge of GPS technology and its integration into analytical processes.
Experience with cloud platforms, specifically Amazon Web Services (AWS).
Familiarity with containerization platforms, including Docker and Kubernetes.
Bachelor's or advanced degree in Computer Science, Data Science, or a related field.
4 plus years’ experience in a similar role
Strong communication and collaboration skills.
Ability to work in a dynamic and fast-paced environment.
**An active Top Secret clearance is required.**
**Great To Have! **
Familiarity with Natural Language Processing (NLP) techniques. Preferred
Working knowledge of generative and agentic Artificial Intelligence models, usage, and training techniques. Preferred.
Full-stack software engineering or development experience. Preferred.
Expertise in blockchain architecture and cryptocurrency data analytics. Preferred.
Understanding of machine learning algorithms and their application in cybersecurity analytics. Preferred.
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