Business Analyst

Job Purpose

• Serve as the lead Business Analyst for the AI Ready Data initiative and AI Enablement projects under the G4-2-4 policy—"Effective Data Provisioning for Expanded AI Application.”
• Responsible for gathering requirements across Proving Ground, Data Governance & Stewardship, and Data Quality & Observability.
• Translate business needs into AI-ready specifications and deliver executive presentations, business cases, and strategic documentation to accelerate AI transformation.
• Collaborate with AI Hub, DSG, and stakeholders to ensure data readiness, governance alignment, and scalable AI adoption.

Key Accountabilities

1. AI Ready Data Requirements & Documentation (35%)

• Lead requirements gathering across:
  • Proving Ground: AWS sandbox, data onboarding, synthetic data, cost models, IAM/S3 integration
  • Data Governance: classification, policies, privacy/risk checklists, stewardship roles
  • Data Quality: profiling, completeness scoring, validation, observability, drift detection
• Write user stories, acceptance criteria (Jira/Confluence, SAFe®)
• Define PoC exit criteria, readiness checklists, and value validation frameworks

2. AI Enablement Strategy & Governance (20%)

• Support 6-step AI readiness framework (objectives → culture)
• Document AI operations readiness: A-DASH standardization, storage policies, process improvements
• Define data requirements for AI-friendly formats, workflows, and automation
• Support Palantir Foundry evaluation: ontology, lineage, integrations
• Develop governance artifacts: responsible AI, model ownership, bias, explainability, compliance

3. Executive Presentations & Strategy (20%)

• Create presentations for leadership, QBRs, and evaluations
• Build business cases and ROI models (including $3M AI budget)
• Develop AI readiness reports, maturity scorecards, and dashboards
• Produce operating models, RACI, process flows, and policy updates
• Maintain RAID logs and weekly status reporting

4. AI Hub Collaboration & Intake (15%)

• Act as liaison to AI Hub and manage use-case intake
• Define intake requirements: governance checks, steward validation
• Document data onboarding for AI (catalog, metadata, marketplace)
• Support vendor POCs and track AI pipeline (10 → 50 themes growth target)

5. DPS Cross-Project Support (10%)

• Support BI and data initiatives (Qlik, Power BI, Informatica, DataPower)
• Assist in observability tool evaluation (Datadog, IBM watsonx)
• Contribute to global alignment (Japan/NA operations, policy updates)

• 5+ years in Business Analysis (IT/data/analytics)

• 2+ years in AI/ML project requirements

• Experience with AWS data platforms (S3, Redshift, Glue, Athena, SageMaker)

• Strong background in business cases, ROI, and executive reporting

• Agile/SAFe® experience with Jira/Confluence

Technical Skills

• PowerPoint, Excel, Word, Visio
• SQL, data catalog & metadata tools
• Data governance, lineage, quality, observability
• BI tools: Power BI, Qlik, Tableau
• AI/ML concepts: lifecycle, feature engineering, synthetic data, ontology, responsible AI