Senior Business Analyst - AI, Analytics & Automation

NTT DATA Services•Dallas, TX

1d•$77,800 - $144,860•Remote

About The Position

NTT DATA is seeking a Senior Business Analyst - AI, Analytics & Automation to join their team. This role involves leading the analysis and documentation of business requirements for AI, analytics, automation, and digital transformation initiatives. The analyst will act as a liaison between business stakeholders and technical teams, analyze business processes for optimization, and support AI/ML solution development. Responsibilities include translating business needs into functional requirements, supporting AI solution development, defining KPIs, analyzing data for insights, and evaluating AI/automation solutions. The role also involves supporting solution design, performing data analysis, working with technical teams on requirements and data flows, participating in the full product development lifecycle, supporting testing phases, and preparing project documentation. Post-implementation, the analyst will support integrations, monitor performance, analyze production issues, and develop user guides and training materials.

Requirements

8+ years of experience as a Business Analyst, Systems Analyst, Product Analyst, or equivalent role in technology-driven environments.
3+ years of experience working with AI/ML concepts, data-driven decision-making, analytics, automation, or modern digital platforms.
5+ years of experience working across the full product/software development lifecycle, including requirements, solution design, testing, UAT, implementation, go-live, and post-production support.
5+ years of experience analyzing complex business processes and translating business needs into functional and technical requirements.
5+ years of experience performing data analysis, defining KPIs, developing or supporting dashboards, and translating analytical findings into actionable business outcomes.
5+ years of experience working with cross-functional teams including engineering, QA, product, data science, and business stakeholders.
5+ years of experience with process analysis, workflow optimization, and identifying opportunities for automation and digital transformation.
Strong understanding of predictive modeling, AI/ML use cases, analytics workflows, intelligent automation, and data-driven solutions.
Strong analytical and problem-solving skills, with the ability to research complex topics, interpret data, identify insights, and make recommendations.
Excellent communication, presentation, facilitation, and stakeholder management skills, with the ability to work effectively at all organizational levels.

Nice To Haves

4+ years of experience with RPA, Intelligent Automation, or AI-enabled process automation, preferably within the healthcare industry.
3+ years of experience or exposure to major cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform (GCP).
Experience working with AI/ML products, analytics platforms, SaaS solutions, or enterprise data platforms.
Experience in product-based or platform-based solution development.
Healthcare domain experience, particularly in Payer, Provider, Revenue Cycle Management (RCM), Coordination of Benefits (COB), healthcare analytics, or related areas.
Experience supporting Generative AI, Agentic AI, Intelligent Automation, or AI-assisted business processes.
Experience developing business cases, ROI analyses, solution roadmaps, or proposals for AI and automation initiatives.
Certifications such as CBAP, CCBA, PMI-PBA, Product Owner, Scrum, or other Agile/Business Analysis certifications are an asset.

Responsibilities

Lead the elicitation, analysis, documentation, and validation of business requirements for AI, analytics, automation, and digital transformation initiatives.
Translate business needs into functional requirements, user stories, process flows, use cases, and acceptance criteria.
Act as the primary bridge between business stakeholders, Product Owners, data scientists, AI/ML teams, engineering, and QA.
Facilitate requirements-gathering and solutioning workshops to align business objectives with technical capabilities.
Analyze existing business processes and identify opportunities for optimization, automation, and AI-driven improvements.
Collaborate with data scientists and AI/ML teams to translate business challenges into practical AI/ML use cases and measurable business outcomes.
Support AI solution development by assisting with data validation, feature inputs, model validation, and interpretation of model outputs.
Help define KPIs, business metrics, measurement frameworks, and success criteria for AI and analytics initiatives.
Analyze data to identify trends, opportunities, anomalies, and insights that support business decision-making.
Support the development of analytics dashboards, reporting frameworks, and decision-support solutions.
Evaluate AI, automation, and analytics solutions from a business and user perspective to ensure they address defined business objectives.
Support solution design activities involving process optimization, intelligent automation, data transformation, and system integration.
Perform data analysis, mapping, validation, transformation, and reconciliation for system inputs and outputs.
Work closely with technical teams to define functional requirements, integration requirements, and data flows.
Participate throughout the product development lifecycle, including requirements, design, development, testing, implementation, and post-production support.
Support functional testing, System Integration Testing (SIT), User Acceptance Testing (UAT), and regression testing.
Develop test scenarios, validate results, document defects, and coordinate issue resolution with technical teams.
Prepare project documentation, requirements artifacts, process documentation, and implementation materials.
Support project planning, status tracking, risk and issue management, and stakeholder communications.
Support integrations between AI/ML solutions, enterprise applications, data platforms, and third-party systems.
Assist with production readiness, implementation planning, and successful deployment of new solutions and enhancements.
Monitor solution performance and business outcomes following implementation.
Analyze production issues, support root-cause analysis, and recommend corrective actions and enhancements.
Work with cross-functional teams to ensure successful product rollouts, adoption, and continuous improvement.
Develop user guides and training materials and conduct stakeholder training as required.