AI/ML & Advanced Analytics Lead

Job Title: AI/ML & Advanced Analytics Lead
Job ID: DCF RFQ 2627 015
Client: State of Florida Department of Children and Families (DCF), Economic Self Sufficiency / Office of Economic Self Sufficiency
Location: Hybrid - Florida Department of Children and Families, Office of Information Technology Services, 2415 N. Monroe Street, Suite 400, Tallahassee, FL 32303 (Hybrid in-person/remote; personnel must be onsite for selected meetings and presentations during the month).
Duration: Anticipated September 14, 2026 through June 30, 2027 (renewals may be available)
Resume Limit: 3 Pages (1 Resume per Role) I. Project Overview

The State of Florida Department of Children and Families (DCF) is seeking an electronic data analytics solution and related professional services to support the Supplemental Nutrition Assistance Program (SNAP) eligibility determination process. The Advanced Analytics and Eligibility Integrity System (AAEIS) is intended to reduce eligibility determination errors, improve program integrity, and generate decision-support recommendations.

II. Role Summary

We are looking for a senior AI/ML and Advanced Analytics professional to lead the design, development, validation, implementation, and monitoring of machine-learning and predictive-analytics capabilities supporting SNAP eligibility determination. This is not a generic Data Scientist role; the candidate must have experience deploying production decision-support models within operational workflows.

III. Key Responsibilities

• Lead the assessment of available data sources, data quality, completeness, integrity, usability, and limitations.
• Perform exploratory and statistical analysis of eligibility-related data.
• Identify, categorize, quantify, and prioritize potential eligibility determination errors, risk indicators, error patterns, trends, correlations, anomalies, and predictive factors.
• Develop predictive analytics and machine-learning models, case-level risk scoring, and prioritization methodologies.
• Generate eligibility decision-support recommendations and confidence scoring mechanisms.
• Develop explainable AI capabilities identifying primary recommendation factors, policy considerations, data elements evaluated, model confidence/limitations, etc.
• Conduct model validation, performance evaluation, and monitor accuracy, precision, recall, false positives/negatives, model drift, demographic impact, and override rates.
• Document training data, feature-selection, validation datasets, and fairness/disparate-impact analysis.
• Perform root-cause analytics for recurring eligibility errors.
• Collaborate with business SMEs, architects, developers, and DCF stakeholders to support UAT, production-readiness, and post-deployment monitoring.

IV. Mandatory Experience & Qualifications

• 8 12+ years of analytics/data-science experience, including 3+ years implementing production ML/predictive solutions.
• Production implementation of predictive models, decision-support recommendation systems, and risk-scoring or classification models.
• Model validation, performance monitoring, and Explainable AI/model interpretability.
• Experience deploying analytics within operational workflows (not just POCs/research).
• Experience with structured government/healthcare/financial/case data.
• Must have experience in at least one regulated environment: Government, Healthcare, Medicaid, SNAP/public benefits, Financial services, Fraud detection, or Case management.
• Provider team must provide three (3) references for similar projects performed within the past five (5) years.

V. Technical Skills

• Python, SQL, Scikit-learn, XGBoost/LightGBM, TensorFlow/PyTorch.
• Predictive modeling, classification, anomaly detection, feature engineering.
• Model validation, model explainability, SHAP/LIME or equivalent approaches.
• ML pipelines, model governance, drift monitoring, data-quality assessment, and statistical analysis.
• Cloud/platform experience (AWS, Azure, GCP, Databricks, Snowflake, or comparable platforms).

VI. Preferred Domain Experience

• Priority candidates will have experience with: SNAP > Medicaid/Public Benefits > Integrated Eligibility > HHS > Fraud/Program Integrity > Healthcare/Financial Assistance.