Data Scientist II

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:

• Analyze large, noisy datasets to identify meaningful patterns that produce actionable results supporting financial crimes investigations.


• Build property graphs from multiple data sources to perform network analytics on individuals, entities, and their support networks.


• Apply statistical analysis and correlate disparate data sources to surface relationships and anomalies.


• Develop probabilistic and/or predictive models to support analytic objectives.


• Implement machine learning processes into production software applications.


• Use big data tools and proprietary data to answer mission and business questions.


• Present findings in written intelligence products of varying lengths, styles, and formats, and communicate complex technical results in plain language for non-technical audiences.


• Participate, in limited cases, in working meetings with FinCEN customers to gather requirements or present findings.

Requirements:

• Top Secret Clearance


• Bachelor’s degree required


• U.S. Citizenship


• 4–7 years of data science experience (Level II).


• Experience using open-source machine learning frameworks such as scikit-learn and TensorFlow to answer business questions using proprietary data.


• Experience with statistical analysis and correlating disparate data.


• Experience with probabilistic and/or predictive modeling.


• Experience performing data analysis using scripting languages such as Python, R, MATLAB, and Spark.


• Experience implementing machine learning processes into production software applications.


• Experience using big data tools to answer business questions with proprietary data.


• Experience building property graphs from multiple data sources to perform network analytics.


• Demonstrated ability to analyze large, noisy datasets and identify meaningful, actionable patterns.


• Strong time management, prioritization, and problem-solving skills in a time-constrained environment, with adaptability to changing priorities, formats, and standards.


• Understanding of proper contractor/government interaction protocols.

Preferred:

• Prior experience using FinCEN’s data