Data Scientist II

Dynamisinc; Vienna (VA); On-site; USD 90,000 - 120,000; Full time

Job summary

Dynamisinc is looking for a Data Scientist II based in Vienna, Virginia, to leverage machine learning and network analytics in combatting financial crimes. This role involves analyzing large datasets and transforming them into actionable intelligence for governmental operations.

Candidates must have a Bachelor's degree, Top Secret Clearance, and 4–7 years of relevant experience, including proficiency in statistical analyses and open-source machine learning frameworks. The position also requires strong analytical skills, adaptability in fast-paced environments, and effective communication.

Qualifications

• Top Secret Clearance.
• 4–7 years of data science experience.
• Experience in open-source machine learning.

Responsibilities

• Analyze large datasets to identify patterns in financial crimes.
• Build property graphs for network analytics.
• Develop predictive models to support analysis.
• Present findings in accessible formats.

Skills

Machine learning frameworks (scikit-learn, TensorFlow)

Data analysis using Python, R, MATLAB, Spark

Statistical analysis

Probabilistic/predictive modeling

Network analytics

Time management

Problem-solving

Education

Bachelor’s degree

Tools

Big data tools

Job description

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