AI Data Analyst

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 strateg...