Sr. Business Analyst- AI Prototyping & Automation

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Inovalon was founded in 1998 on the belief that technology, and data specifically, would empower the transformation of the entire healthcare ecosystem for the better, improving both outcomes and economics. At Inovalon, we believe that when our customers are successful in their missions, healthcare improves. Therefore, we focus on empowering them with data-driven solutions. And the momentum is building. Together, as ONE Inovalon, we are a united force delivering solutions that address healthcare's greatest needs. Through our mission-based culture of inclusion and innovation, our organization brings value not just to our customers, but to the millions of patients and members they serve. Overview: Inovalon is seeking a Sr. Business Analyst - AI Agent Operator to join its AI Prototyping & Automation team. This role combines analytical rigor with hands-on AI execution. The Sr. Business Analyst identifies and quantifies AI automation opportunities across the enterprise and builds the working prototypes that validate them. Rather than handing specifications to a separate build team, this analyst proves the business case by shipping a functional prototype that stakeholders can evaluate and engineering can productionize. This is a hybrid role for analysts fluent in modern AI tooling - people who can do the financial modeling and stakeholder work of a traditional Sr. BA and also use AI tooling to prototype and demonstrate solutions before committing to engineering investment. Production builds, ongoing maintenance, and operational ownership of deployed systems sit with engineering and AI Operations counterparts. This is a fast-moving environment where priorities shift, requirements are often ambiguous, and the tooling evolves weekly. The right person for this role is energized by that - not frustrated by it. They ask questions, chase context on their own, learn new tools before being asked to, and treat uncertainty as a starting condition rather than a blocker. Duties and Responsibilities: Opportunity Identification & Business Cases Maintain a pipeline of AI automation opportunities sourced from business unit intake, executive priorities, and direct stakeholder discovery. Build business cases with quantified ROI: cost savings, revenue lift, hours offloaded, quality improvements. Translate ambiguous business problems into well-scoped automation candidates with clear acceptance criteria. Track opportunity status, prioritization, and outcomes against original projections. Prototype & Validate Build functional prototypes of proposed agents and automations using modern AI tooling (LLM coding assistants, agent frameworks, prompt and skill libraries). Validate or invalidate business cases by getting a working version in front of stakeholders within days, not quarters. Iterate prototypes against real user feedback before committing to engineering investment. Produce demo-ready artifacts that move executive decisions forward. Hand off validated prototypes to engineering with clear specifications, success criteria, and stakeholder context. Impact Tracking Deliver monthly executive reports covering pipeline health, in-flight initiatives, and realized impact. Conduct post-implementation reviews comparing projected to actual ROI; capture lessons that improve future estimates. Other Responsibilities Maintain compliance with Inovalon's policies, procedures, and mission statement. Adhere to all confidentiality and HIPAA requirements in accordance with Inovalon Operating Policies and Procedures. Fulfill additional responsibilities reasonably assigned to support the operational and financial success of Inovalon. Job Requirements: 5+ years in business analysis, management consulting, product operations, or analyst roles. Hands-on experience using LLMs and agent tooling - prompting, evaluations, and workflow orchestration. Candidates should be prepared to walk through a prototype they have built. Working proficiency in Python and SQL: sufficient to query databases, parse API responses, manipulate structured data, and debug agent workflows - not expected to write production backend code. Strong financial acumen: ROI modeling, sensitivity analysis, cost-benefit frameworks. Strong written and verbal communication; comfortable in front of executives and engineers alike. Intrinsic curiosity and a bias toward action; comfortable operating with incomplete information, learning new tools independently, and moving quickly in ambiguous environments. Experience with modern agent frameworks (LangGraph, AutoGen, MCP, or equivalent) preferred. Domain knowledge in a compliance-heavy industry such as healthcare, financial services, or insurance preferred. Background in product management, business operations, or technology consulting preferred. Familiarity with continuous improvement methodologies is a plus. Experience in healthcare IT, SaaS, or highly regulated industries is a plus. Education: Bachelor's or Master'

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