Senior Data Scientist
Company: SMX Services & Consulting, Inc.
Customer: U.S. Small Business Administration, Office of Inspector General
Division: Technology Solutions Division
Openings: Two
SMX Labor Category: Data Scientist
Employment Type: Full-time, direct employment
Anticipated Program Start: September 15, 2026
Security Designation: Public Trust
Citizenship: Must be a U.S. citizen
CompensationCompensation elementAmountEmployee pay range $82.29-$84.97 per hour
The annual equivalent is based on 2,080 hours. Final employee compensation will be established within the range based on verified experience, education, certifications, qualifications, and SMX approval.
Location
Telework eligible from an SMX- and Government-approved worksite within the United States.
The employee must be available to participate in onsite meetings, training, collaborative sessions, job-shadowing, or other customer activities in the Washington, D.C. area when requested. The PWS authorizes routine full-time or part-time telework but allows the Government to revoke telework authorization if security, performance, productivity, or operational requirements are not met.
Work Schedule
This is a full-time position. Work must be performed within the Government operating window of:
6:00 a.m. to 6:00 p.m. Eastern Time, Monday through Friday
The exact daily schedule will be established according to program coverage requirements. Employees are not expected to work a 12-hour shift unless separately approved. Overtime requires advance Government approval.
Position Summary
SMX Services & Consulting, Inc. is seeking two Senior Data Scientists to support the SBA Office of Inspector General Technology Solutions Division.
The Senior Data Scientists will develop advanced analytical solutions supporting federal audits and criminal investigations. Work will focus on loan fraud, financial fraud, improper payments, misuse of Government funds, program noncompliance, and other investigative or oversight matters.
The selected professionals will work with existing data assets, source-code repositories, analytical models, data pipelines, and cloud services developed by SBA OIG and previous contractors.
Direct-Employment Requirement
This position supports a pending federal task-order quotation.
Primary Responsibilities
The Senior Data Scientist will:
- Provide senior-level and authoritative guidance on advanced analytical methods.
- Analyze source-table quality and identify abnormalities, inconsistencies, missing information, and reliability concerns.
- Review, maintain, validate, and support existing SBA OIG loan-fraud indicators.
- Develop repeatable methods for combining and analyzing large relational, structured, semi-structured, and unstructured datasets.
- Collaborate directly with criminal investigators to develop and execute analytical strategies supporting loan-fraud investigations.
- Adjust analytical approaches as investigative requirements and case priorities change.
- Identify and clearly communicate data-quality issues and analytical limitations.
- Handle protected investigative information in accordance with federal criminal-procedure and evidentiary requirements, including Rule 6(e) when applicable.
- Design, develop, test, calibrate, and implement advanced statistical models.
- Develop supervised and unsupervised machine-learning models.
- Develop regression, classification, clustering, Bayesian, ensemble, and related analytical models.
- Identify anomalies, relationships, patterns, subpopulations, and predictive variables.
- Build and test predictive models addressing financial fraud, improper payments, abuse, or noncompliance within SBA programs.
- Generate and refine investigative leads from analytical and machine-learning outcomes.
- Develop, tune, and deploy production machine-learning models supporting loan-fraud detection.
- Coordinate with data engineers to ensure cloud architecture efficiently supports analytical models and production pipelines.
- Develop and scale natural-language-processing solutions for large text collections.
- Process structured, semi-structured, and unstructured data.
- Use optical character recognition, semantic-similarity methods, and Government-approved LLM capabilities when appropriate.
- Develop network graphs, interactive maps, dashboards, reports, and analytical visualizations.
- Prepare technical explanations of analytical methods, model behavior, assumptions, limitations, and results.
- Prepare data summaries and visual products for investigators and auditors.
- Prepare executive-level summaries and recommendations for SBA OIG leadership.
- Maintain detailed documentation for test models, production models, methodology, code, and results.
- Preserve analytical records consistent with applicable evidentiary requirements.
- Automate analytical and business processes using Python, Microsoft Excel, Power BI, Power Apps, SharePoint, and other approved technologies.
- Identify new investigative or business questions that expand the value of SBA OIG analysis and reporting.
Required Education or Equivalent Experience
Each candidate must meet one of the following requirements:
- Master's degree, Ph.D., doctorate-level equivalent, or higher degree in data science, machine learning, computer science, mathematics, or a related field; or
- At least 10 years of applied professional experience in one or more of those fields.
Required Five-Year Experience
Each candidate must possess at least five years of hands-on experience in each of the following:
- Designing, implementing, and maintaining advanced artificial-intelligence systems and predictive models.
- Developing supervised machine-learning models.
- Developing unsupervised machine-learning models.
- Developing analytical rules and models using leading-edge analytical tools and recognized best practices.
- Developing regression, classification, and other statistical models.
- Using statistical and machine-learning methods to identify anomalies, patterns, relationships, and predictive variables.
Required Three-Year Experience
Each candidate must possess at least three years of hands-on experience in each of the following:
- Providing data support for criminal investigations involving financial fraud or abuse of Government funds.
- Manipulating and analyzing data using Python.
- Using Pandas for production analytical work.
- Working in a modern cloud environment, including Azure, AWS, or GCP.
Cloud certifications are preferred.
Required Two-Year Experience
Each candidate must possess at least two years of hands-on experience in each of the following:
- Conducting advanced SQL data analysis using Microsoft SQL Server.
- Conducting advanced SQL data analysis using PostgreSQL.
- Developing and scaling natural-language-processing solutions.
- Presenting analytical methods and findings to technical stakeholders.
- Presenting analytical methods and findings to nontechnical stakeholders.
- Communicating results orally, in writing, and through visualizations.
These are the minimum qualifications
Preferred Qualifications
- Azure, AWS, or GCP certification.
- Experience supporting federal law-enforcement investigations.
- Experience supporting Inspectors General, auditors, investigators, or oversight organizations.
- Experience developing loan-fraud or financial-fraud models.
- Experience developing analytical products used to generate criminal-investigative leads.
- Experience with Azure Machine Learning and Azure Synapse.
- Experience using Power BI and Power Apps.
- Experience using OCR and semantic-similarity techniques.
- Experience integrating LLMs with existing enterprise data assets.
- Experience deploying and monitoring production machine-learning models.
- Experience working with criminal-evidentiary data and documentation requirements.
Required Technical Skills
- Python
- Pandas
- Microsoft SQL Server
- PostgreSQL
- Supervised machine learning
- Unsupervised machine learning
- Regression and classification
- Statistical modeling
- Natural-language processing
- Data visualization
- Cloud analytics using Azure, AWS, or GCP
- Analytical documentation
- Technical and executive communication
Citizenship and Security Requirements
Candidates must:
- Be U.S. citizens. This is an SMX hiring requirement for this position.
- Possess a valid Social Security number.
- Be eligible for a Public Trust background investigation.
- Receive a favorable Entry on Duty determination before beginning Government performance.
- Be able to obtain required SBA accounts, credentials, badges, and system access.
- Comply with SBA and SBA OIG security, privacy, data-handling, and evidence-protection requirements.
The employee may work with unclassified but sensitive and administratively controlled SBA OIG information, personally identifiable information, and protected criminal-investigative information.
The employee must:
- Access Government data only through Government-furnished equipment or approved SBA interfaces.
- Never download or store PII on non-Government-furnished equipment.
- Protect Government credentials, devices, data, and PIV cards.
- Use privileged access only when authorized and based on need to know.
- Follow all SBA and SBA OIG security and privacy policies.
- Promptly report security, access, equipment, or privacy incidents.
AI and Software Restrictions
- Contractor-owned software, code assistants, and developer utilities may not be used in the SBA OIG environment without written authorization.
- AI and LLM workflows must operate only in SBA-approved environments.
- SBA OIG data, source code, schemas, investigative information, or internal procedures may never be submitted to public cloud-based LLM services.
Resume Submission Requirements
Applicants should provide a resume that clearly identifies:
- Employment dates by month and year.
- Degree, institution, field, and graduation date.
- Years of advanced AI and predictive-modeling experience.
- Years of supervised and unsupervised machine-learning experience.
- Years supporting criminal investigations involving financial fraud or Government funds.
- Years of Python and Pandas experience.
- Years of Azure, AWS, or GCP experience.
- Years of SQL Server and PostgreSQL experience.
- Years developing and scaling NLP solutions.
- Specific projects and individual responsibilities.
- Quantifiable results, such as fraud leads generated, dollars identified or recovered, investigations supported, prosecutions assisted, model-accuracy improvements, or work hours saved.