Business Analyst-AI Prototyping & Automation

Inovalon

11h•Hybrid

About The Position

This role combines analytical rigor with hands-on AI execution. The 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 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.

Requirements

3+ 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
Applicants must be authorized to work in the United States as a condition of employment.

Nice To Haves

Bachelor’s or Master’s in Business, Engineering, Computer Science, or related field
Experience with modern agent frameworks (LangGraph, AutoGen, MCP, or equivalent)
Domain knowledge in a compliance-heavy industry such as healthcare, financial services, or insurance
Background in product management, business operations, or technology consulting
Familiarity with continuous improvement methodologies

Responsibilities

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
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
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