Source description
About the role
Dynamis is seeking a Data Scientist II to apply machine learning, statistical analysis, and network analytics to BSA data and other Government-provided data sources in support of FinCEN's efforts to combat financial crimes—including terrorist financing, proliferation financing, cyber-crime, and complex money laundering. Backed by Dynamis's deep bench of financial intelligence and data science expertise, the Data Scientist II transforms large, disparate datasets into actionable results and clear, decision-ready intelligence products that support FinCEN's policy, law enforcement, regulatory, and other customers, working under the technical direction of FinCEN Program Managers.
Responsibilities
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• Analyze large, noisy datasets to identify meaningful patterns that produce actionable results supporting financial crimes investigations.
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• Build property graphs from multiple data sources to perform network analytics on individuals, entities, and their support networks.
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• Apply statistical analysis and correlate disparate data sources to surface relationships and anomalies.
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• Develop probabilistic and/or predictive models to support analytic objectives.
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• Implement machine learning processes into production software applications.
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• Use big data tools and proprietary data to answer mission and business questions.
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• Present findings in written intelligence products of varying lengths, styles, and formats, and communicate complex technical results in plain language for non-technical audiences.
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• Participate, in limited cases, in working meetings with FinCEN customers to gather requirements or present findings.
Requirements
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• Top Secret Clearance
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• Bachelor’s degree required
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• U.S. Citizenship
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• 4–7 years of data science experience (Level II).
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• Experience using open-source machine learning frameworks such as scikit-learn and TensorFlow to answer business questions using proprietary data.
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• Experience with statistical analysis and correlating disparate data.
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• Experience with probabilistic and/or predictive modeling.
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• Experience performing data analysis using scripting languages such as Python, R, MATLAB, and Spark.
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• Experience implementing machine learning processes into production software applications.
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• Experience using big data tools to answer business questions with proprietary data.
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• Experience building property graphs from multiple data sources to perform network analytics.
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• Demonstrated ability to analyze large, noisy datasets and identify meaningful, actionable patterns.
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• Strong time management, prioritization, and problem-solving skills in a time-constrained environment, with adaptability to changing priorities, formats, and standards.
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• Understanding of proper contractor/government interaction protocols.
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Preferred:
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• Prior experience using FinCEN’s data
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