Senior Data Scientist – AI-ML, Anomaly Detection Lead

Chameleon Integrated Services

Senior Data Scientist leading explainable AI/ML anomaly detection for Chameleon’s Florida government oversight platform. Modernizing rules, validating models, and quantifying fraud, waste, and abuse risks.

Posted 8/12/2026part-timeRemote • 🇺🇸 United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates advanced expertise in machine learning engineering and data analytics, with a strong focus on developing and deploying transparent algorithms and predictive models for government applications. Proficient in Python and SQL, with a proven ability to produce audit-ready documentation and technical artifacts.

Highest-signal resume keywords

Machine Learning EngineeringData AnalyticsPython MasterySQL ProficiencyModel Evaluation

ATS Keywords

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Hard Skills

Machine Learning AlgorithmsPredictive ModelingStatistical ForecastingFeature EngineeringAnomaly DetectionRisk Scoring ModelsData Drift DetectionThreshold CalibrationTechnical DocumentationAudit-Ready Validation

Certifications & Qualifications

FDLE Level II Background Screening

Industry Keywords

Government CustomerData ScienceFinancial DataProcurement DataContract ManagementPurchasing-Card Ledger Data

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Evaluate, enhance, and modernize the existing 11-rule baseline POC library for enterprise scalability
Architect transaction-centric anomaly logic, including data features, risk scoring models, tolerance thresholds, and alert prioritization
Develop, refine, and deploy supervised and unsupervised machine learning algorithms
Maintain transparent, non-black-box algorithms with human-readable explanations and evidence for auditors and investigators
Establish audit-ready validation datasets and document accuracy, false-positive metrics, and rule reproducibility
Provide technical documentation, test scripts, and system logs for independent technical reruns
Implement automated criteria for model scoring transparency, version control, feature mapping, and data drift detection
Engineer formulas and methodologies to quantify cost avoidance, financial recoveries, risk exposure, and investigative referrals

Requirements

What you’ll need

10+ years of comprehensive data analytics and data science experience
5+ years of dedicated, hands-on machine learning engineering
Documented delivery of data science, predictive modeling, or advanced analytics solutions in federal, state, military, or local government
Advanced hands-on mastery of Python and SQL
Deep expertise in supervised and unsupervised learning, classification, clustering, statistical forecasting, and advanced feature engineering
Experience in model evaluation, threshold calibration, and false-positive/false-negative impact analysis
Ability to translate model outputs into defensible, audit-ready forensic evidence
Experience producing technical artifacts, configuration baselines, and model documentation for independent replication
Experience with disparate transaction-level financial, procurement, contract management, or purchasing-card ledger data
Must be a U.S.-based citizen or resident currently living inside the United States
Must successfully clear an FDLE Level II background screening, including fingerprinting, within 5 business days of contract award
Resume must explicitly document government customer, problem, technical approach, personal contribution, deployment/validation status, and quantifiable outcomes

Benefits

Comp & perks

Opportunity to work on revolutionary federal IT infrastructure
Opportunity to grow alongside cutting-edge technology
Promoting from within
Equal opportunity employment