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AI Data Analyst

Job in Tucson, Pima County, Arizona, 85718, USA
Listing for: Maximus
Full Time position
Listed on 2026-03-01
Job specializations:
  • IT/Tech
    Data Analyst, AI Engineer, Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
  • 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.
  • 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.
  • 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.
  • 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, Tensor Flow 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…
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