Sr. Business Analyst- AI Prototyping & Automation

📍 Job Overview

Job Title: Sr. Business Analyst - AI Prototyping & Automation

Company: Inovalon

Location: Remote - United States

Job Type: Full-Time

Category: Revenue Operations / Sales Operations / GTM Operations (AI & Automation Focus)

Date Posted: May 29, 2026

Experience Level: 5-10 Years

Remote Status: Fully Remote

🚀 Role Summary

• Drive the identification and quantification of AI automation opportunities across Inovalon's enterprise by building compelling business cases with clear ROI projections, integrating GTM strategy with operational efficiency.

• Develop and validate functional AI prototypes using modern AI tooling, effectively demonstrating the potential of proposed automations to stakeholders and engineering teams.

• Translate complex, ambiguous business challenges into well-defined automation candidates, establishing clear acceptance criteria to ensure successful validation and potential productionization.

• Track and report on the health of the AI automation pipeline, the progress of in-flight initiatives, and the realized impact against original projections, ensuring alignment with strategic business objectives.

• Collaborate closely with business units, executive leadership, and engineering counterparts to ensure AI automation efforts are aligned with market needs and operational excellence.

📝 Enhancement Note: This role is positioned within an AI Prototyping & Automation team, bridging traditional Business Analysis with hands-on AI development. It requires a candidate who can not only perform financial modeling and stakeholder management but also leverage AI tools to build functional prototypes, demonstrating a strong aptitude for operationalizing AI within a complex, regulated industry like healthcare. The emphasis on "shipping a functional prototype" before engineering investment is a key differentiator, highlighting a need for rapid validation and a bias for action.

📈 Primary Responsibilities

• Proactively identify and maintain a pipeline of AI automation opportunities by actively engaging with business units, understanding executive priorities, and conducting direct stakeholder discovery sessions.

• Construct comprehensive business cases that quantify Return on Investment (ROI), including cost savings, revenue uplift, hours offloaded from manual processes, and quality improvements.

• Translate vague business problems into precisely scoped automation candidates with clearly defined acceptance criteria, ensuring alignment with operational and GTM goals.

• Monitor and report on the status, prioritization, and ultimate outcomes of all AI automation opportunities, comparing realized impact against initial projections.

• Build and iterate on functional prototypes of proposed AI agents and automations using contemporary AI tooling such as LLM coding assistants, agent frameworks, and prompt/skill libraries.

• Validate or invalidate business cases rapidly by delivering working prototypes to stakeholders for evaluation within days, not quarters, accelerating the decision-making process.

• Iterate on prototypes based on direct user feedback to refine functionality and ensure alignment with business needs before committing significant engineering resources.

• Produce compelling, demo-ready artifacts that effectively communicate the value proposition and drive executive decisions forward.

• Facilitate the seamless hand-off of validated prototypes to engineering teams, providing clear specifications, success criteria, and essential stakeholder context for production build and operationalization.

• Deliver monthly executive reports that provide a clear overview of pipeline health, the status of in-flight initiatives, and the tangible impact achieved relative to initial forecasts.

• Conduct thorough post-implementation reviews to compare projected ROI against actual results, capturing critical lessons learned to enhance the accuracy of future estimates and operational efficiency.

• Ensure strict adherence to Inovalon’s policies, procedures, and mission statement, maintaining compliance with all confidentiality and HIPAA requirements.

• Fulfill additional responsibilities as reasonably assigned to support the operational and financial success of Inovalon, demonstrating flexibility and a commitment to team objectives.

📝 Enhancement Note: The responsibilities emphasize a dual focus: strategic business analysis (opportunity identification, business cases, ROI) and tactical AI execution (prototyping, validation, iteration). This blend is crucial for a role that aims to bridge the gap between conceptual AI opportunities and demonstrable, production-ready solutions, directly impacting operational efficiency and potentially revenue generation through automation.

🎓 Skills & Qualifications

Education:

Experience:

Required Skills:

• Hands-on AI Tooling Proficiency: Demonstrated experience using modern AI tools, including LLMs, agent frameworks (e.g., LangGraph, AutoGen, MCP), prompt engineering, and workflow orchestration, with readiness to present a functional prototype.

• Programming & Data Manipulation: Working proficiency in Python and SQL, sufficient for querying databases, parsing API responses, manipulating structured data, and debugging agent workflows. Production-level coding is not expected, but practical application is key.

• Financial Acumen & ROI Modeling: Strong capability in developing ROI models, conducting sensitivity analyses, and applying cost-benefit frameworks to business cases, essential for quantifying the impact of automation initiatives.

• Communication & Stakeholder Management: Excellent written and verbal communication skills, with the ability to effectively engage and present to both executive leadership and technical engineering teams, ensuring clear understanding and buy-in.

• Adaptability & Proactiveness: Intrinsic curiosity, a strong bias toward action, comfort operating with incomplete information, and the ability to learn new tools independently and move swiftly in ambiguous, fast-paced environments.

Preferred Skills:

• Agent Framework Expertise: Prior experience with modern agent frameworks such as LangGraph, AutoGen, or MCP, indicating a deeper understanding of AI system architecture and orchestration.

• Industry Domain Knowledge: Familiarity with compliance-heavy industries like healthcare, financial services, or insurance, providing context for regulatory requirements and operational nuances.

• Product Management/Operations Background: Experience in product management, business operations, or technology consulting, offering insights into product lifecycle, operational strategy, and client-facing solutions.

• Continuous Improvement Methodologies: Familiarity with continuous improvement frameworks (e.g., Lean, Six Sigma) to drive process optimization and efficiency gains.

• Healthcare IT/SaaS Experience: Background in healthcare IT, SaaS, or other highly regulated industries, demonstrating an understanding of complex system integrations and data governance.

📝 Enhancement Note: The requirement for "hands-on experience using LLMs and agent tooling" and the expectation to "walk through a prototype they have built" are critical. This signals that the role is not purely theoretical but requires practical, demonstrable skills in building AI solutions, a key differentiator for operations roles focused on innovation and efficiency.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• AI Prototype Demonstrations: Showcase functional AI prototypes built using LLMs and agent frameworks, illustrating problem-solving capabilities and technical execution in a tangible format.

• Business Case & ROI Analysis: Provide examples of business cases developed for operational improvements or new initiatives, clearly detailing financial modeling, ROI calculations, and projected impact.

• Process Mapping & Optimization: Include documentation or case studies demonstrating the analysis and optimization of business processes, highlighting efficiency gains or workflow improvements achieved.

• Data Analysis & Reporting Artifacts: Present examples of data analysis, insightful reports, or dashboards that effectively communicate performance metrics, trends, and actionable recommendations.

Process Documentation:

• Workflow Design & Automation: Demonstrate experience in designing, documenting, and implementing automated workflows, whether through traditional RPA, scripting, or AI-driven agent orchestration.

• System Integration & Data Flow: Illustrate understanding of how different systems interact and how data flows between them, especially in the context of automating processes that span multiple platforms.

• Performance Measurement & Feedback Loops: Show examples of how processes were monitored for performance, how feedback was incorporated, and how continuous improvement was achieved post-implementation.

📝 Enhancement Note: Given the role's focus on rapid prototyping and validation, a portfolio should emphasize demonstrable AI prototypes. Candidates should be prepared to walk through their creations, explain the underlying logic, and articulate the business value they aim to deliver. This is distinct from a traditional BA portfolio that might focus solely on requirements documents.

💵 Compensation & Benefits

Salary Range:

Benefits:

• Comprehensive Health Coverage: Includes health insurance options to support associate well-being.

• Life Insurance: Provides financial security for associates and their families.

• Company-Paid Disability: Offers income protection in case of disability.

• Retirement Savings Plan: A 401k plan to help associates save for long-term financial goals.

• Generous Paid Time Off: Over 18 days of paid time off annually, allowing for work-life balance and rejuvenation.

• Performance-Based Incentives: Potential eligibility for performance-based incentives, aligning compensation with individual and company success.

Working Hours:

• Standard working hours are expected to be around 40 hours per week, with potential for flexibility depending on project needs and operational demands.

📝 Enhancement Note: The provided salary range ($95,000 - $144,000 USD) for a Sr. Business Analyst with AI Prototyping & Automation experience, especially in a remote US setting, aligns with industry benchmarks for mid-to-senior level roles in technology and operations. This range reflects the specialized skills in AI tooling, programming, and business analysis required. The benefits package is standard for a large, established tech company, emphasizing health, financial security, and work-life balance.

🎯 Team & Company Context

🏢 Company Culture

Industry: Healthcare Technology (Health-Tech) and Data Analytics, focusing on improving healthcare outcomes and economics through data-driven solutions. Inovalon operates in a highly regulated environment, requiring a strong emphasis on compliance, data security, and accuracy.

Company Size: Inovalon is a significant player in the health-tech industry, with a substantial employee base that suggests a structured organization with established processes, but also opportunities for impact within specialized teams.

Founded: 1998, indicating a company with a long history and deep expertise in its field, having evolved significantly with technological advancements.

Team Structure:

• AI Prototyping & Automation Team: This specialized team likely consists of business analysts, AI engineers, data scientists, and potentially product managers focused on identifying, prototyping, and validating AI-driven automation solutions.

• Reporting Structure: The Sr. Business Analyst will likely report to a Manager or Director of AI Prototyping & Automation, with close collaboration across various business units, product teams, and the central engineering/AI Operations departments.

• Cross-Functional Collaboration: Expect extensive collaboration with stakeholders from different business units (e.g., operations, finance, product) to gather requirements, solicit feedback, and ensure prototypes meet actual business needs. Close partnership with engineering and AI Operations is critical for successful hand-offs and productionization.

Methodology:

• Data-Driven Decision Making: Emphasis on leveraging data to identify opportunities, build business cases, and measure impact.

• Agile Prototyping & Iteration: A rapid, iterative approach to building and validating AI solutions, focusing on quick feedback loops to refine prototypes before significant investment.

• ROI-Focused Validation: All initiatives are expected to demonstrate clear financial benefits or operational efficiencies, with a strong emphasis on quantifying ROI.

• Continuous Learning & Adaptation: The fast-evolving nature of AI tools and techniques necessitates a culture of continuous learning and adaptation to new technologies and methodologies.

Company Website: https://www.inovalon.com/

📝 Enhancement Note: Inovalon's focus on healthcare implies a need for candidates to understand or quickly learn about data privacy (HIPAA), regulatory compliance, and the specific operational challenges within the healthcare ecosystem. The company's mission to improve outcomes and economics through technology is a key cultural driver.

📈 Career & Growth Analysis

Operations Career Level: This Sr. Business Analyst role represents a mid-to-senior level position. It requires a blend of analytical expertise, practical AI implementation skills, and the ability to influence stakeholders. It's a pivotal role for individuals looking to specialize in the rapidly growing field of AI-driven operations and automation within a complex industry.

Reporting Structure: The role likely reports into a management layer overseeing AI strategy and implementation, with direct interaction with senior leaders across business units and engineering. This provides visibility and opportunities to influence strategic decisions regarding automation investments.

Operations Impact: The primary impact of this role is through identifying and validating AI-driven process improvements that lead to significant cost savings, increased efficiency, enhanced data accuracy, and potentially new revenue streams or improved service delivery within Inovalon's healthcare solutions. By proving the ROI of AI prototypes, this role directly influences capital allocation for technology development and operational transformation.

Growth Opportunities:

• Specialization in AI/ML Operations: Deepen expertise in AI agent development, prompt engineering, and AI platform management, becoming a go-to expert in Inovalon's AI initiatives.

• Transition to AI Product Management or Engineering: With proven success in prototyping and validation, there's a pathway to move into roles focused on productizing AI solutions or leading AI engineering teams.

• Leadership in Automation Strategy: Grow into leadership positions overseeing broader automation strategies, managing teams of analysts, and driving enterprise-wide digital transformation efforts.

• Cross-Functional Mobility: Develop a broad understanding of Inovalon's various business units, opening doors to roles in strategic operations, business development, or even client-facing advisory positions leveraging AI expertise.

📝 Enhancement Note: The "Sr." title implies expectations of leadership potential and independent work. Candidates demonstrating strong problem-solving, initiative, and the ability to mentor or guide others (even informally) will be highly valued. Growth paths are clearly tied to the expanding AI landscape within Inovalon.

🌐 Work Environment

Office Type: As a fully remote role, the "office" is the associate's home workspace. Inovalon supports this by providing necessary tools and potentially stipends for home office setup. Occasional travel to Inovalon office locations or industry events may be required.

Office Location(s): While the role is remote within the United States, Inovalon has physical office locations which may serve as hubs for occasional team meetings, collaboration sessions, or company events. Specific locations are not detailed but would typically include major business centers.

Workspace Context:

• Remote Collaboration Tools: Heavy reliance on digital collaboration tools (e.g., Slack, Microsoft Teams, Zoom, collaborative document platforms) to maintain connectivity and productivity.

• Access to AI & Development Tools: Associates will require reliable access to cloud-based AI platforms, development environments, and secure connections to Inovalon's internal systems and data repositories.

• Independent Work & Team Integration: The environment fosters independent work, requiring self-discipline and time management, balanced with active participation in virtual team meetings, brainstorming sessions, and project updates.

Work Schedule:

• The role is typically a 40-hour work week. Flexibility is expected, especially given the fast-paced nature of AI development and the need to collaborate across different time zones within the US. This flexibility allows for focused deep work periods and responsive engagement with team members and stakeholders.

📝 Enhancement Note: The remote nature emphasizes the need for strong self-management skills, proactive communication, and effective use of virtual collaboration tools. Candidates should highlight their experience working effectively in a distributed team environment.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: HR or a recruiter will conduct an initial screening to assess basic qualifications, cultural fit, and understanding of the role's core requirements.

• Technical/Skills Assessment: This stage will likely involve a hands-on exercise or a detailed discussion focusing on your proficiency with AI tooling, Python, SQL, and financial modeling. Be prepared to demonstrate your ability to prototype and analyze.

• Case Study Presentation: Candidates may be asked to present a portfolio piece or a hypothetical solution to a business problem, demonstrating their analytical process, prototyping skills, and communication effectiveness. This is where your AI prototype will be key.

• Hiring Manager Interview: A discussion with the hiring manager to delve deeper into experience, problem-solving approach, and how you fit within the team's dynamics and Inovalon's culture.

• Cross-Functional / Stakeholder Interviews: Interviews with potential collaborators from business units or engineering teams to assess interpersonal skills, collaboration style, and ability to translate technical concepts for diverse audiences.

• Final Round / Executive Interview: Potentially an interview with a senior leader to discuss strategic alignment, long-term vision, and overall fit for the organization.

Portfolio Review Tips:

• Highlight AI Prototypes: Prioritize showcasing functional AI prototypes. Be ready to demo them live or provide clear video walkthroughs, explaining the problem, your solution, the tools used, and the intended business impact.

• Quantify Impact: For all portfolio examples, clearly articulate the quantifiable results achieved (e.g., % reduction in processing time, $ saved, % increase in accuracy). Use metrics that resonate with business objectives.

• Structure Your Narrative: For each project, follow a clear story: the problem, your approach (analysis, prototyping, iteration), the solution, and the outcomes. Emphasize your role and contributions.

• Showcase Problem-Solving: Demonstrate how you tackle ambiguity, identify root causes, and iterate on solutions based on feedback and data.

• Tailor to Inovalon: If possible, subtly tailor your examples to showcase experience relevant to healthcare, compliance, or data-intensive operations.

Challenge Preparation:

• AI Prototyping Challenge: Expect a scenario where you need to conceptualize and outline the steps to prototype an AI solution for a given business problem. If time permits in the interview, you might even be asked to code a small part of it.

• Business Case Development: Be ready to discuss how you would build a business case for an AI automation initiative, including identifying key metrics, potential risks, and stakeholder buy-in strategies.

• Technical Problem Solving: Prepare for questions involving Python or SQL, focusing on data manipulation, querying efficiency, and debugging common issues in data processing or API interactions.

📝 Enhancement Note: The emphasis on "walking through a prototype" suggests that candidates should have a well-prepared, functional demonstration ready. This is a critical component that sets this role apart from traditional analyst positions. The interview process is designed to test both technical AI skills and business acumen.

🛠 Tools & Technology Stack

Primary Tools:

• AI Agent Frameworks: LangGraph, AutoGen, MCP, or similar platforms for orchestrating AI agents and complex workflows. Proficiency in at least one is crucial.

• LLM Interaction Tools: Experience with various LLM providers (e.g., OpenAI, Anthropic, Google AI) and tools for prompt engineering, fine-tuning (if applicable), and managing API calls.

• Programming Languages: Python (essential for scripting, data manipulation, and agent development), SQL (for data extraction and analysis).

• Version Control: Git and GitHub/GitLab for code management and collaboration.

Analytics & Reporting:

• Data Querying & Analysis: SQL clients, potentially BI tools like Tableau, Power BI, or Looker for data exploration and visualization.

• Spreadsheet Software: Advanced Excel or Google Sheets for financial modeling, sensitivity analysis, and ad-hoc reporting.

• Reporting Platforms: Tools for generating monthly executive reports on pipeline health and impact tracking.

CRM & Automation:

• CRM Systems: Familiarity with CRM platforms (e.g., Salesforce) might be beneficial for understanding sales/customer data context, though not explicitly required.

• Workflow Automation Tools: Experience with other automation tools or platforms could be a plus, demonstrating a broader understanding of process automation.

• Integration Platforms: Understanding how different systems connect and exchange data is valuable, even if not directly hands-on with specific integration tools.

📝 Enhancement Note: The explicit mention of LLM coding assistants, agent frameworks, and prompt/skill libraries points to a modern AI development stack. Candidates should be prepared to discuss their hands-on experience with these specific types of tools, beyond just theoretical knowledge.

👥 Team Culture & Values

Operations Values:

• Innovation & Agility: A strong emphasis on exploring new AI technologies, rapidly prototyping solutions, and adapting to the fast-evolving AI landscape.

• Data-Driven Impact: A core belief in using data and analytics to identify opportunities, measure success, and drive tangible business outcomes.

• Collaboration & Transparency: Open communication and close teamwork across business units and engineering to ensure alignment, share knowledge, and achieve collective goals.

• Accountability & Ownership: Taking responsibility for identifying opportunities, building effective prototypes, and clearly demonstrating their value and impact.

• Customer Focus: Ultimately, all initiatives are aimed at improving customer (internal or external) outcomes and economics, reflecting Inovalon's mission.

Collaboration Style:

• Cross-Functional Integration: A highly collaborative approach, working closely with business stakeholders to understand needs, with engineering to ensure feasibility and production readiness, and with AI Operations for ongoing management.

• Feedback-Driven Iteration: A culture that encourages and actively seeks feedback on prototypes to refine solutions and ensure they meet user requirements and business objectives.

• Knowledge Sharing: Encouraging team members to share learnings about new AI tools, techniques, and best practices to foster collective growth and efficiency.

📝 Enhancement Note: Inovalon's "mission-based culture of inclusion and innovation" suggests a drive towards purposeful work and embracing new ideas. The emphasis on "ONE Inovalon" points to a desire for cohesive teamwork across departments.

⚡ Challenges & Growth Opportunities

Challenges:

• Rapid Tool Evolution: The AI landscape changes weekly; staying current with the latest LLMs, agent frameworks, and best practices requires continuous learning and adaptation.

• Ambiguity & Incomplete Information: Dealing with ill-defined business problems and evolving requirements is inherent in AI prototyping; learning to navigate this uncertainty is key.

• Bridging Technical & Business Divides: Effectively communicating complex AI concepts to non-technical stakeholders and translating business needs into technical requirements for AI development.

• Demonstrating Tangible ROI: Proving the financial viability and operational impact of AI prototypes can be challenging, requiring robust modeling and clear articulation of benefits.

• Balancing Prototyping Speed with Quality: The need to ship functional prototypes quickly must be balanced with ensuring they are robust enough to provide meaningful validation and a clear path to production.

Learning & Development Opportunities:

• Cutting-Edge AI Skills: Direct experience with state-of-the-art AI tools, agent frameworks, and prompt engineering techniques.

• Industry Expertise: Developing deep knowledge in healthcare IT, compliance, and data analytics within a regulated industry.

• Cross-Functional Exposure: Gaining broad understanding across Inovalon's business units and their operational challenges.

• Mentorship & Career Pathing: Opportunities to learn from experienced AI professionals and explore career paths in AI product management, engineering leadership, or strategic operations.

• Continuous Learning Resources: Access to training, conferences, and internal knowledge-sharing sessions to stay ahead of AI trends.

📝 Enhancement Note: The challenges highlight the need for resilience, adaptability, and a proactive learning mindset. The growth opportunities are significant for individuals passionate about the intersection of AI, operations, and business strategy.

💡 Interview Preparation

Strategy Questions:

• "Describe a complex business problem you solved using AI prototyping. What tools did you use, what was the outcome, and what would you do differently next time?" (Focus on your prototype, the process, and lessons learned.)

• "How do you approach building a business case for an AI automation initiative, especially when dealing with uncertain ROI or rapidly evolving technology?" (Emphasize your financial acumen and risk assessment.)

Company & Culture Questions:

• "What interests you about Inovalon's mission and its work in the healthcare industry?" (Research Inovalon's mission, values, and recent news.)

• "How do you handle working in a fast-paced, ambiguous environment where priorities can shift rapidly?" (Showcase your adaptability and bias for action.)

Portfolio Presentation Strategy:

• The "Problem-Solution-Impact" Framework: For each portfolio item, clearly articulate the business problem, the AI solution you prototyped, the tools/techniques used, and the quantifiable business impact (ROI, efficiency gains, etc.).

• Live Demo or Detailed Walkthrough: Be prepared to demo your AI prototype live or provide a comprehensive walkthrough, explaining the logic, user flow, and key functionalities.

• Focus on Your Contribution: Clearly define your specific role and contributions within any team projects.

• Be Ready for Technical Deep Dives: Anticipate questions about your code, chosen frameworks, prompting strategies, and data handling.

📝 Enhancement Note: Candidates should prepare to demonstrate not just what they can build, but how they approach building it, why they make certain technical or business decisions, and how they measure success. The portfolio is your primary tool for this.

📌 Application Steps

To apply for this operations position:

• Submit your application through the Inovalon careers portal using the provided link.

• Tailor Your Resume: Highlight experience with AI prototyping, LLMs, agent frameworks, Python, SQL, and ROI modeling. Quantify achievements wherever possible, using metrics relevant to operational efficiency and business impact.

• Prepare Your Portfolio: Curate 2-3 key projects that showcase your AI prototyping capabilities, business case development, and analytical skills. Be ready to demonstrate a functional AI prototype.

• Research Inovalon: Understand Inovalon's mission, its role in the healthcare industry, and its commitment to innovation and data-driven solutions. This will help tailor your responses and demonstrate genuine interest.

• Practice Your Pitch: Rehearse your ability to articulate complex technical concepts and business value clearly and concisely, especially when presenting your portfolio and responding to strategy questions.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.