Financial Crime Data Scientist — Secret Clearance

Guidehouse; Washington (District of Columbia); On-site; USD 98,000 - 163,000; Full time

Benefits offered by this job

Medical Insurance

Dental & Vision Insurance

401(k) Plan

Parental Leave

Tuition Reimbursement

Mobility Stipend

Short-Term Disability

Long-Term Disability

Employee Referral Program

Emergency Back-Up Childcare

Job summary

Guidehouse is seeking a skilled data science professional to lead analytical workstreams in support of financial crime investigations. You will apply advanced methodologies to structured and unstructured data to detect illicit activity and produce analytical products for regulators and enforcement agencies.

The role requires active Secret clearance, US citizenship, and a strong background in Python, SQL, PySpark, ML, NLP, and data visualization.

Qualifications

• ACTIVE and CURRENT Secret clearance required.

Responsibilities

• Lead analytical workstreams supporting complex financial crime investigations and enforcement matters.
• Apply advanced data science methodologies to structured and unstructured datasets to identify patterns of illicit financial activity, support investigative findings, and develop analytical products used in regulatory and enforcement decision-making.

Skills

Python

SQL

PySpark

Machine Learning

Natural Language Processing

Data Visualization

Statistical Analysis

Entity Resolution

Education

Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Economics, Finance, Criminal Justice, Intelligence Studies, or related field

Tools

Hive

Spark

PostgreSQL

Oracle

Job description

Guidehouse is seeking a skilled data science professional to lead analytical workstreams in support of financial crime investigations. You will apply advanced methodologies to structured and unstructured data to detect illicit activity and produce analytical products for regulators and enforcement agencies.

The role requires active Secret clearance, US citizenship, and a strong background in Python, SQL, PySpark, ML, NLP, and data visualization.