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 crimesincluding 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
• Bachelors degree required
• U.S. Citizenship
• 47 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 FinCENs data