Data Scientist

Omniscius; Washington, Northern (District of Columbia, KY); Hybrid; USD 140,000 - 200,000; Full time

Job summary

Omniscius seeks an experienced Data Scientist to support a FinCEN program in Washington, DC. The role applies advanced data science, statistical modeling, and machine learning to large-scale financial datasets for detecting financial crime.

The ideal candidate will be hands-on with Python and R, AWS cloud-native tech, and SQL, able to translate regulatory requirements into robust analytical models and clearly communicate findings to stakeholders.

Qualifications

• 8+ years of overall professional experience.
• 4-5+ years as a Data Scientist.
• Strong background in statistical modeling and ML.
• Hands-on Python and R programming.
• Experience with Python data science tools (Jupyter, PySpark, Pandas).
• Strong SQL skills with large datasets.
• Hands-on AWS cloud-native services (S3, RDS, OpenSearch, Lambda).
• Experience with large-scale structured and unstructured data.
• Familiarity with BSA data and regulatory requirements.
• Ability to translate requirements into analytical models.
• Technical documentation and stakeholder communication.
• Bachelor's degree in a quantitative field.

Responsibilities

• Design, develop, validate, and deploy ML models on BSA/AML data.
• Develop analytical approaches for detecting suspicious activity.
• Perform EDA, feature engineering, statistical analysis, and model validation.
• Build data science solutions using Python, Jupyter, PySpark, Pandas, and R.
• Use SQL to query large datasets and derive insights.
• Work with data stored in AWS tools (S3, RDS, OpenSearch, Lambda).
• Collaborate with analysts and stakeholders to translate requirements into models.
• Create visualizations and communicate findings to technical and non-technical audiences.
• Document pipelines, methodologies, and findings per standards.
• Engage in code reviews and promote reproducible workflows.
• Contribute to continuous improvement of analytical methods.

Skills

Python

R

Machine learning

Statistical modeling

SQL

AWS

Big data

BSA/AML domain knowledge

Education

Bachelor's degree in Engineering, Data Science, Statistics, Mathematics, Computer Science or related quantitative field

Tools

Jupyter Notebook

PySpark

Pandas

OpenSearch

S3

RDS

Lambda

PostgreSQL

Job description

Data Scientist

Location: Washington, DC
Work Arrangement: 100% Onsite - 5 Days per Week
Clearance: Active Top Secret with SCI Eligibility
Citizenship: U.S. Citizenship Required; No Dual Citizenship

Position Overview

Our client is seeking an experienced Data Scientist to support a U.S. Department of the Treasury Financial Crimes Enforcement Network (FinCEN) program in Washington, DC. This position will apply advanced data science, statistical modeling, and machine learning techniques to large-scale financial datasets in support of financial crime detection and analysis.

The ideal candidate will have strong hands-on experience with Python, R, machine learning, AWS cloud-native technologies, and large-scale data analysis. Experience working with Bank Secrecy Act (BSA), Anti-Money Laundering (AML), or related financial crime data is highly preferred.

Key Responsibilities

• Design, develop, validate, and deploy machine learning models and statistical algorithms to identify financial crime patterns using BSA/AML transaction data.

• Develop analytical approaches for detecting activities such as structuring, layering, smurfing, and other potentially suspicious financial behavior.

• Perform exploratory data analysis, feature engineering, statistical analysis, and model validation.

• Develop data science solutions using Python, Jupyter Notebook, PySpark, Pandas, R, and related technologies.

• Use SQL to perform complex queries and analyze large-scale structured and unstructured datasets.

• Work with data stored and processed through AWS services, including S3, PostgreSQL RDS, OpenSearch, Lambda, and related cloud-native technologies.

• Collaborate with compliance analysts, investigators, and technical stakeholders to translate regulatory and investigative requirements into data analyses and analytical models.

• Develop visualizations and communicate analytical findings to both technical and non-technical stakeholders.

• Document data pipelines, analytical methodologies, model logic, assumptions, and findings in accordance with agency and organizational standards.

• Participate in peer code reviews and contribute to best practices for reproducible, maintainable data science workflows.

• Support continuous improvement of analytical models and methodologies used to identify financial crime risks and patterns.

Required Qualifications

• 8+ years of overall professional experience.

• 4-5+ years of professional experience working as a Data Scientist.

• Strong experience with statistical modeling and machine learning.

• Hands-on programming experience with Python and R.

• Experience with Python data science tools and frameworks, including Jupyter Notebook, PySpark, and Pandas.

• Strong SQL skills with experience performing complex queries against large datasets.

• Hands-on experience with AWS cloud-native services such as S3, RDS, OpenSearch, and Lambda.

• Experience analyzing large-scale structured and unstructured datasets.

• Working knowledge of Bank Secrecy Act (BSA) data.

• Ability to translate business, regulatory, and investigative requirements into analytical approaches and models.

• Experience producing technical documentation and communicating analytical findings to diverse audiences.

• Bachelor's degree in Engineering, Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field.

Preferred Experience

• Experience supporting FinCEN, the U.S. Department of the Treasury, or another Federal financial/regulatory organization.

• Experience working with BSA/AML datasets.

• Understanding of financial crime and Anti-Money Laundering methodologies.

• Experience developing models designed to identify structuring, layering, smurfing, or other suspicious transaction patterns.

• Experience collaborating directly with financial crime investigators, compliance analysts, or regulatory personnel.

• Experience developing data science solutions within secure Federal environments.

Clearance & Citizenship Requirements

• Must possess an active Top Secret clearance with eligibility for access to Sensitive Compartmented Information (SCI).

• Interim clearances of any type will not be accepted.

• Must be a U.S. Citizen.

• Dual citizenship is not permitted for this position.

Work Location

This position is located in Washington, DC and requires onsite work five days per week. There is no telework or remote option.