Data Scientist

4–5 years of work experience as a data scientist with strong knowledge of statistical modeling and machine learning experience using Python and R

Active Top-Secret clearance with eligibility for access to Sensitive Compartmented Information (SCI)

Hands-on experience with AWS cloud-native services (e.g., S3, RDS, OpenSearch, Lambda)

Working knowledge of Bank Secrecy Act (BSA) data

Demonstrated experience with SQL for complex querying and analysis of large-scale structured and unstructured datasets

Expertise in Python, Jupyter Notebook, R, NumPy, Pandas, and Scikit-Learn

$90,000-130,000

The salary range for this position represents the anticipated hiring range. Actual compensation will be determined based on factors such as relevant experience, skills, education, certifications, and potential contract funding.

Design, develop, and deploy machine learning models and statistical algorithms to detect financial crime patterns (e.g., structuring, layering, smurfing) using BSA/AML transaction data

Perform exploratory data analysis, feature engineering, and model validation using Python, Jupyter Notebook, PySpark, Pandas, and R

Use SQL for complex querying and analyze large-scale structured and unstructured datasets stored in AWS S3, PostgreSQL RDS, and OpenSearch

Work with large data environments storing financial transactions or other critical data, including performing entity resolution across large datasets

Understand the structure of bank wire transfer data, including international formats from message systems such as SWIFT, CHIPS, and book transfer systems, as well as BSA-derived data such as SARs, CTRs, and 8300s

Ensure data quality and integrity through data mapping, cleaning, and validation processes