Lead Financial Crime Data Scientist – Investigations

Guidehouse

Washington

On-site

USD 98,000 - 163,000

Full time

8 days ago

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Benefits offered by this job

Medical, Rx, Dental & Vision Insurance

Parental Leave and Adoption Assistance

401(k) Retirement Plan

Tuition Reimbursement, Personal Dev &

Mobility Stipend

Employee Referral Program

Corporate Sponsored Events & Community

Short-Term & Long-Term Disability

Job summary

Guidehouse is seeking a Senior Financial Crimes Data Scientist to lead analytical workstreams supporting complex investigations and enforcement matters. You will apply advanced data science to structured and unstructured datasets to identify patterns of illicit activity and develop analytical products used in regulatory decisions.

You will need a current Secret clearance, U.S. citizenship, and expertise with Python, SQL, Spark, ML, NLP, and large-scale data environments.

Qualifications

ACTIVE and CURRENT Secret clearance required.
Must be U.S. Citizen.
Four (4) years of experience developing analytical methods, models, tools, or workflows that deliver actionable insights.
Experience analyzing financial data and BSA filings, including SARs, CTRs, wire transfers, transaction records, account activity, or related financial intelligence datasets.
Strong proficiency with Python, SQL, PySpark, machine learning, natural language processing, data visualization, and statistical analysis.
Experience performing entity resolution of businesses, companies, beneficial owners, or related parties using analytical techniques and methodologies.
Experience working in large-scale data environments utilizing Hive, Spark, Hadoop, PostgreSQL, Oracle, or similar technologies.
Experience translating analytical findings into memoranda, briefings, recommendations, or other decision-support products.
Ability to independently execute analytical projects and collaborate directly with investigators, intelligence analysts, attorneys, and regulatory stakeholders.
Willing to work onsite in Washington, DC five (5) days per week.

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

Hive/Spark/Hadoop

PostgreSQL/Oracle

Independent work

Collaboration

Education

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