Data Scientist

Omniscius Consulting; Washington (District of Columbia); On-site; USD 140,000 - 190,000; Full time

Job summary

Omniscius Consulting seeks a data scientist to apply ML to analyze financial transaction data for a federal bureau. On-site in Washington, DC, you will build models to identify suspicious patterns and support money laundering investigations.

Responsibilities include model development in Python/R, AWS data engineering, collaboration with compliance analysts, and ensuring reproducible pipelines with proper documentation.

Qualifications

• Top Secret SCI clearance required.
• Bachelor’s Degree or higher in a related field from an accredited university.
• 4+ years of data science experience building and deploying ML models.

Responsibilities

• Design, develop, and deploy machine learning models to detect financial crime patterns.
• Perform data analysis and feature engineering on AWS infrastructure (S3, RDS, OpenSearch).
• Collaborate with compliance analysts and investigators to translate regulatory requirements into models and clear reports.
• Build maintainable data pipelines, document model logic, and conduct code reviews.

Skills

Data science experience

SQL proficiency

Education

Bachelor’s Degree or higher in a related field

Tools

Python

R

PySpark

Pandas

SQL

AWS

OpenSearch

S3

Job description

In this role, you will apply data science and machine learning to analyze complex financial transaction data for a major federal intelligence and law enforcement bureau. Your analytical models will help identify suspicious patterns, supporting efforts to safeguard the financial system from illicit activity and money laundering. This work would be performed on-site in Washington, DC.

Key Responsibilities:

• Financial Crime Pattern Detection:Designing, developing, and deploying machine learning models and statistical algorithms to identify complex money laundering techniques - such as structuring, layering, and smurfing - within massive financial datasets.
• Cloud-Native Data Engineering & Analysis:Performing exploratory data analysis, feature engineering, and model validation using Python, PySpark, and SQL across scalable AWS infrastructure, including S3, RDS, and OpenSearch.
• Stakeholder Collaboration & Translation:Partnering directly with compliance analysts and federal investigators to translate complex regulatory requirements into high-impact analytical models and clear visual reports.
• Model Integrity & Workflow Standardization:Building maintainable data pipelines, documenting model logic to agency standards, and leading peer code reviews to ensure reproducible, high-quality data science practices.

Required Qualifications:

• Active Top Secret SCI clearance
• Bachelor’s Degree or higher in a related field from an accredited college or university
• 4+ years of dedicated data science experience building, validating, and deploying machine learning models using Python and/or R.
• Hands‑on experience analyzing Bank Secrecy Act (BSA) or Anti‑Money Laundering (AML) transaction data to detect illicit financial patterns.
• Hands‑on experience executing queries and managing data pipelines within AWS cloud environments (e.g., S3, RDS/PostgreSQL, OpenSearch, Lambda).
• Strong proficiency with SQL and big‑data frameworks (e.g., PySpark, Pandas) to analyze large-scale structured and unstructured datasets.

Preferred Qualifications:

• Experience building intuitive data dashboards and clear visual reports to present findings to non‑technical operational teams.
• Demonstrated track record of establishing automated model documentation and reproducible data pipelines in a regulated environment.