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Elite Technical

AI/ML Analyst

Career Insights for Business Intelligence Analyst

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What they do

A Business Intelligence Analyst collects and analyzes data that provides an accurate picture of business operations and performance for a company. Completes statistical analysis of current and historic business data, identifies trends and develops projections. Presents data analysis that informs planning and strategic decision making for a company.

$91,141 / year median in Maryland

+11% projected growth

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Job Description

The AI/ML Business Data Analyst plays a critical role in translating business needs into data driven, AI enabled solutions that will drive strategic decisions across our client's corporate landscape. This role partners closely with IT, and business units across the organization, to identify opportunities where data, machine learning, and automation can responsibly enhance operations. The AI Data Business Analyst will emphasize practical application of analytics and AI, ensuring solutions are explainable, compliant, and aligned our client's values. The analyst bridges business context and technical execution, turning complex datasets into insights that drive measurable outcomes. The incumbent will collaborate with all levels of the Health Plan and will recommend solutions based on identified data trends and business needs. This role will also be responsible for creating documentation and maintaining visualizations based on business requirements.
PRIMARY ACCOUNTABILITIES
  • Business & Data Analysis
  • Partner with business stakeholders to understand operational challenges and translate them into clear data and analytics requirements.
  • Analyze large, complex datasets to identify trends, risks, and improvement opportunities.
  • Develop business cases and ROI narratives for analytics and AI initiatives that improve efficiency, reduce errors, or enhance member experience.
  • AI & Advanced Analytics Enablement
  • Collaborate with IT to produce analysis dashboards, to create visualizations for the organization.
  • Support the design, testing, and deployment of machine learning and AI enabled use cases for approved initiatives.
  • Assist in monitoring models post deployment, identifying data quality issues, bias risks, or performance drift.
  • Governance, Compliance & Risk Awareness
  • Adhere to Compliance requirements related to data handling and reporting requirements.
  • Document data sources, logic, assumptions, and limitations to support audits, transparency, and explainability.
  • Participate in responsible AI and data governance processes, ensuring ethical use of analytics across the organization.
  • Coordinate with IT Team Leads in conjunction with the IT Project Manager, to align with organization priorities.
  • Work with external vendors to develop and maintain approved solutions. Scope business functional enhancement projects and validate recommended solutions to the organization. Required Skills
  • Bachelors degree in business Analytics, Data Science, Information Systems, Statistics, Computer Science, or a related discipline, or equivalent practical experience.
  • 5+ years of experience in AI / ML data analysis, business analysis, or analytics roles, within a healthcare insurance/payor environment.
  • Hands-on experience working with structured datasets and analytical tools to support business decision-making.
  • Experience collaborating with cross-functional teams, including IT, compliance, and operations.
  • Excellent technical and analytical skills.
  • Excellent verbal and written communication skills. Ability to render and write business requirements such as technical documentation and business decision documentation.
  • Proficiency in requirements gathering
  • effectively translating business needs as expressed by users into workable specs, estimating time/duration to complete and implement the solution.
TECHINICAL SKILLS
  • Strong SQL and data analysis skills; experience with BI and visualization tools.
  • Strong experience in Machine Learning and AI concepts (predictive modeling, NLP, automation), with emphasis on business application rather than model development.
  • Ability to clearly communicate insights, risks, and recommendations to non-technical audiences.
PREFERRED QUALIFICATIONS
  • Exposure to model governance, audit support, or regulatory reporting.
  • Experience supporting analytics during high volume periods such as Open Season.