India
Most AI systems fail at consulting not because of bad algorithms but because they've never sat across a client in a strategy session, written a business case under pressure, or had an MD redline their case study at midnight. I have 16 years across Deloitte, Mubadala sovereign wealth fund, Deutsche Bank, and VMware, delivering strategic analysis, business transformation, and consulting engagements for C-suite clients across Financial Services, Retail, and Enterprise Technology. What I do that's harder to find than it looks: · I can read an AI-generated business scenario and tell you exactly where the reasoning breaks down, not just that it's wrong, but why, and what a senior consultant would have written instead. · I've reviewed and scored hundreds of complex case studies, strategic frameworks, and transformation documents to exacting quality standards. Zero errors in client-facing work across 8 consecutive Deloitte engagements. · I've evaluated LLM outputs against real consulting benchmarks and produced structured written feedback that reduced reasoning errors by ~30% in production AI systems. If you're building AI that needs to think like a management consultant, and you need someone who actually is one, let's talk.
• Applied management consulting methodologies including hypothesis-driven analysis, issue trees, and structured problem-solving to define enterprise transformation scope and advise U.S. and global clients on AI-enabled operating model redesign. • Scored, reviewed, and refined AI-generated business scenarios, strategic frameworks, and client-facing case studies against established consulting standards; produced structured written and verbal feedback that improved model reasoning accuracy by ~30% across evaluation cycles. • Identified logical inconsistencies and reasoning gaps in AI outputs; documented findings with evidence-based commentary and proposed targeted corrections directly mirroring the evaluation and feedback workflow required for AI training. • Collaborated remotely with cross-functional teams spanning product management, data science, and engineering across U.S. and Asia-Pacific time zones; embedded consulting rigor into AI model training and evaluation workflows. • Delivered board-level presentations with exceptional written clarity translating complex analytical findings into executive narratives for C-suite stakeholders; received consistent commendation for communication precision and attention to detail. • Redesigned Tier-1 client workflows through process improvement and AI integration, reducing handle times ~65% and improving self-service adoption ~50%; responsible AI compliance requirements observed throughout.
• Led strategic consulting portfolio for a sovereign wealth fund (Mubadala) initiative across market segmentation, customer intelligence, virtual advisory, and talent strategy delivering measurable commercial outcomes across all workstreams. • Developed, reviewed, and quality-assured business case documentation, analytical frameworks, and transformation roadmaps; applied rigorous accuracy checks and consulting methodology standards before submission to executive sponsors. • Systematically evaluated AI and LLM model outputs against real-world management consulting benchmarks; scored outputs on reasoning quality, factual accuracy, and strategic relevance producing written feedback reports used to retrain and improve models. • Directed organizational transformation program with independently verified outcomes: customer retention +20%, revenue growth +15%, operational cost reduction −30%; presented results to board-level sponsors with detailed written reporting. • Established responsible AI governance frameworks including data privacy controls, bias monitoring, drift detection, and audit logging embedded across all AI deployments at the sovereign wealth fund level. • Coached and mentored cross-functional remote teams of consultants, data scientists, and engineers; established written quality standards, peer review processes, and structured feedback loops across all engagement deliverables.
• Delivered end-to-end Big 4 management consulting engagements for Retail and CPG clients business case development, strategic analysis, process redesign, and supply-chain optimization generating +12–15% measurable sales uplift. • Produced and reviewed high-quality, client-ready consulting deliverables: case studies, analytical frameworks, scenario analyses, and transformation roadmaps all meeting Deloitte quality assurance standards before C-level presentation. • Conducted structured, criteria-based assessment of AI and analytics model outputs evaluating strategic relevance, logical soundness, and business applicability; wrote detailed review commentary used to improve model and analyst output quality. • Advised clients on responsible AI strategy, regulatory compliance requirements, and governance architecture; ensured all AI-related recommendations aligned with industry best practices and applicable regulatory standards. • Embedded reusable consulting frameworks, methodology accelerators, and written quality review checklists across engagement teams improving delivery consistency, output rigor, and team communication standards. • Demonstrated exceptional attention to detail in all written deliverables; zero material errors flagged in client-facing documents across 8 consecutive engagements.
• Led product analytics; developed price-optimization models and executive KPI frameworks increasing profit margins ~10% combining advanced quantitative analysis with commercially actionable strategic recommendations. • Produced data-driven business cases and board-ready written reports communicated to senior leadership; maintained rigorous standards of analytical accuracy and written precision throughout. • Worked remotely and cross-functionally with product, finance, and engineering teams across multiple geographies; designed performance dashboards enabling evidence-based strategic decision-making at leadership level.
• Enhanced credit-scoring models in a high-scrutiny regulated environment (Deutsche Bank); produced model performance case studies, complex risk scenario analyses, and governance documentation reviewed and approved by senior risk executives. • Applied exceptional written analytical standards risk scenario outputs required zero tolerance for ambiguity or error; all written reports passed internal audit review without material revision. • Collaborated with risk and compliance leadership to design and embed model governance frameworks, automated monitoring controls, and audit logging establishing responsible AI practices before the term was widely adopted.