What are the responsibilities and job description for the Data Scientist II position at Dynamis, Inc.?
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:
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.
- 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.
- Prior experience using FinCEN's data