SENIOR DATA SCIENTIST (US Citizen, Fraud Analytics / Criminal Investigations)

SENIOR DATA SCIENTIST (US Citizen, Fraud Analytics / Criminal Investigations)

*Full-Time | Remote | U.S. Citizenship Required*

What a Strong Candidate Looks Like

If you dont have fraud investigation in your background, it's not you. The ideal candidate is a US Citizen capable of passing a federal Public Trust background investigation that has built fraud detection pipelines that fed directly into investigative or prosecutorial workflows — not just flagged anomalies for business teams. Direct, hands-on experience supporting criminal fraud or abuse investigations is the single most important qualifier for this role. Experience in federal law enforcement, inspector general, financial crimes, or regulatory enforcement data environments will stand out significantly. NLP experience applied to unstructured investigative records, case notes, or financial filings is a major differentiator, as is a demonstrated track record of turning fraud model outputs into leads that investigators actually acted on.

Overview

We are seeking an experienced Senior Data Scientist to lead fraud detection and investigative data analytics in support of a federal oversight mission. This role sits at the center of identifying fraud, waste, and abuse through advanced machine learning and direct analytical support to criminal investigations. This is a long-term engagement with a base period of one year and up to four option years. Work is performed remotely with close collaboration with investigation teams.

What You Will Do

You will design, build, and maintain fraud analytic models and advanced AI/ML systems that detect fraud, abuse, and anomalous patterns in complex federal datasets. You will work directly alongside investigators and analysts, providing hands-on data support to active criminal investigations into fraud and abuse — this is not adjacent analytics work, but direct investigative support where your models and findings inform case direction. You will develop regression, classification, and statistical models purpose-built for anomaly and fraud pattern detection, and you will develop and refine NLP solutions that extract investigative leads from unstructured data sources such as case notes, financial filings, and communications records. Day-to-day work includes Python-based data manipulation, SQL querying across relational environments, and operating within a modern cloud platform.

Translate complex analytical findings into clear, compelling narratives for both technical and non-technical audiences, including investigative staff and executive leadership, using visualizations, dashboards, and written summaries that communicate not just what the data shows but why it matters and what action it supports.

Required Qualifications

Every item below is required. Applications that do not meet all qualifications will not be considered.

• 5 or more years of experience developing fraud analytic rules and models — this must be documented professional experience building fraud detection systems, not adjacent analytics work.
• 3 or more years of experience providing data analytics support for criminal investigations into fraud or abuse — experience working directly with investigators, prosecutors, or law enforcement data environments is required. This is a core, non-negotiable qualification for this role.
• 5 or more years of experience developing regression, classification, and statistical models specifically for anomaly detection and fraud pattern recognition.
• 5 or more years of experience designing, implementing, and maintaining advanced AI/ML predictive models, including both supervised and unsupervised learning methods, applied to fraud and abuse detection use cases.
• Master's degree, Ph.D., or equivalent in data science, machine learning, computer science, mathematics, statistics, or a closely related field — OR a minimum of 10 years of applied hands-on experience in the same disciplines in lieu of a degree.
• 2 or more years designing and scaling Natural Language Processing solutions in production environments, ideally applied to unstructured investigative or case-file data.
• 3 or more years of hands-on data manipulation in Python with Pandas required specifically; NumPy and scikit-learn experience expected.
• 3 or more years operating in modern cloud environments — Azure, AWS, or GCP; multi-cloud experience preferred.
• 2 or more years of advanced SQL development with demonstrated experience in both SQL Server and PostgreSQL specifically; both are required.
• 2 or more years presenting analytical findings to mixed audiences including technical teams, program leadership, and senior non-technical stakeholders, in both written and oral formats.
• U.S. citizenship required. Must be eligible for and able to obtain a federal Public Trust background investigation. Candidates with an existing Public Trust determination are strongly preferred.

Preferred

* Federal Agency Work History

Pay: $60.00 - $70.00 per hour

Work Location: Remote