AI Data Analyst

General Information

Date: Monday, February 23, 2026

City: Remote

Country: United States

Working time: Full-time

Description & Requirements

The AI Data Analyst supports Maximus programs by applying advanced analytics, machine learning, and business intelligence to transform operational data into meaningful insights. This role blends traditional data analytics responsibilities with emerging AI capabilities to accelerate decision-making, improve performance outcomes, and scale analytical maturity across the organization.

This is a fully remote position. Requires 5% travel.

Why Join Maximus?

• 💰 Competitive Compensation - Bonus opportunities based on performance.
• 🛡️ Comprehensive Insurance Coverage - Choose from various plans, including Medical, Dental, Vision, Prescription, and partially funded HSA. Additionally, enjoy Life insurance benefits and discounts on Auto, Home, Renter's, and Pet insurance.
• 🌟 Future Planning - Prepare for retirement with our 401K Retirement Savings plan and Company Matching.
• 🏝️ Unlimited Time Off Package - Enjoy UTO, Holidays, and sick leave.
• 🌱 Holistic Wellness Support - Access resources for physical, emotional, and financial wellness through our Employee Assistance Program (EAP).
• 🏆 Recognition Platform - Acknowledge and appreciate outstanding employee contributions.
• 📚 Tuition Reimbursement - Invest in your ongoing education and development.
• 🎁 Employee Perks and Discounts - Additional benefits and discounts exclusively for employees.
• 🌟 Maximus Wellness Program and Resources - Access a range of wellness programs and resources tailored to your needs.
• 📚 Professional Development Opportunities - Participate in training programs, workshops, and conferences.

Essential Duties and Responsibilities:

• Perform hands-on data analysis and modeling with huge data sets.
• Apply data mining, NLP, and machine learning (both supervised and unsupervised) to improve relevance and personalization algorithms.
• Work side-by-side with product managers, software engineers, and designers in designing experiments and minimum viable products.
• Discover data sources, get access to them, import them, clean them up, and make them “model-ready.” Create and refine features from the underlying data.
• Run regular A/B tests, gather data, perform statistical analysis, draw conclusions on the impact of your optimizations and communicate results to peers and leaders.
• Explore new design or technology shifts in order to determine how they might connect with the customer benefits we wish to deliver.

AI‑Enhanced Analytics & Insight Generation

• Develop, deploy, and operationalize advanced analytical and AI/ML models to uncover trends, identify anomalies, and produce predictive and prescriptive insights.
• Apply machine learning techniques (regression, classification, clustering, NLP, time-series forecasting) to support strategic decision-making and operational efficiency.
• Serve as a subject matter expert on AI‑supported analytics, guiding internal stakeholders on appropriate methodology, data quality considerations, model limitations, and responsible AI use.

Data Analysis, KPI Development & Reporting

• Analyze large volumes of structured and unstructured data and translate findings into clear, actionable insights for leaders, program teams, and business development partners.
• Design, implement, and maintain new KPIs, intelligent metrics, and automated analytical scripts used across dashboards and operational reporting frameworks.
• Perform feature engineering, statistical testing, and exploratory analysis to support model development and performance measurement.

Power BI, Dashboarding & Data Products

• Design, build, and maintain interactive dashboards in Power BI, leveraging AI‑assisted capabilities such as automated insights, anomaly detection, and forecast visualizations.
• Enhance reporting workflows through semantic modeling, DAX optimization, and integration with Microsoft Fabric or other enterprise analytics platforms.

Automation, Low‑Code Solutions & AI Tooling

• Use Power Automate, Power Apps, and AI Builder to automate workflows, streamline data processes, and develop intelligent low‑code applications.
• Build AI‑enabled tools such as semantic search features, automated classification engines, natural‑language query interfaces, or document‑processing models.

Technology Enablement & Collaboration

• Stay current with emerging technologies, including Microsoft Fabric, Azure AI/Cognitive Services, Azure Machine Learning, and other platforms used across Maximus.
• Promote responsible AI principles, documenting processes and advocating best practices across teams.
• Support team communication and strategy through documentation, presentations, training materials, and collaborative planning activities.
• Participate in project management tasks including planning, execution, retrospectives, and performance tracking.

Minimum Requirements

• Bachelor's degree in relevant field of study and 3+ years of relevant professional experience required, or equivalent combination of education and experience.
• Advanced degree in Computer Science, Information Systems, Business Analytics, Mathematics, Statistics, Engineering, Business Administration or a related field preferred.
• 1-3+ years of professional experience with applying quantitative research in optimizing human decisions using technologies like machine learning and/or deep learning.
• 1+ years using major machine learning/deep learning frameworks (e.g., Scikit-learn, PyTorch, TensorFlow and Keras) and algorithms (e.g., CNN, GAN, LSTM, RNN, XGBOOST).
• 1+ years of data engineering experience with modern big data analytics architectures (Hadoop, SQL, HIVE, Spark, Snowflake, etc.) on major cloud platforms (e.g., AWS, Azure, Google Cloud).
• 1+ years programming skill in Python, Scala, or Julia.
• Working knowledge with modern cloud-based data storage and compute environments (e.g., AWS Sagemaker, Databricks in Azure, AI-platform in GCP, etc.).
• Experience deploying ML models into discovery/production environment to drive insights using MLOps a plus.
• Experience working in an agile delivery model a plus.
• Demonstrated leadership and self-direction. Willingness to both teach others and learn new techniques.
• Ability to communicate complex ideas in a clear, precise, and actionable manner.
• Excellent communication and presentation skills, with the ability to articulate new ideas and concepts to technical and non-technical partners.
• PowerBI experience a plus.

Program Specific Requirements:

Minimum Requirements

• Experience developing analytics or ML solution
• Proficiency in Power BI, SQL, DAX, data modeling, and visualization best practice
• Experience analyzing large datasets and presenting insights to technical and non‑technical audiences
• Understanding of Responsible AI governance, model evaluation, and MLOps practices

Preferred Qualifications

• Experience with Azure Machine Learning, Cognitive Services, Databricks, Microsoft - Fabric, or similar cloud‑based AI/analytics tools
• Experience deploying machine learning models in production environments
• Familiarity with Power Platform AI Builder, Copilot capabilities, or generative AI tooling
• Experience working with governance on new tools

Home Office Requirements:

• Reliable high-speed internet service
• Minimum 20 Mpbs download speeds/50 Mpbs for shared internet connectivity
• Minimum 5 Mpbs upload speeds

Key skills/competency

• Advanced Analytics
• Machine Learning
• Data Modeling
• Power BI
• SQL
• Python
• NLP
• Cloud Platforms (Azure, AWS, GCP)
• MLOps
• Statistical Analysis