Jenngang Shih
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Enterprise AI & Analytics Consultant | ML, LLM & GenAI | From Strategy to Production Systems
Enterprise AI & Analytics Consultant with 20+ years of experience designing, delivering, and advising on analytics, machine learning, and Generative AI solutions in large enterprise environments. Works at the intersection of business objectives and technical implementation, helping organizations translate strategic goals into practical, scalable AI and analytics systems. My background began in business and finance before transitioning into computer science and engineering, which continues to shape how I approach analytics and AI as a bridge between business intent and technical execution. Brings deep experience across predictive analytics, NLP, Generative AI, and enterprise BI platforms, with domain exposure in human resources, finance, and customer relationship management. Known for a thoughtful, execution-oriented approach that emphasizes clarity of use cases, sound data foundations, and solutions that move from exploration into real operational use. CORE COMPETENCIES - Enterprise AI & GenAI Strategy - LLMs, NLP, RAG, Agent Architectures - Predictive Analytics & Statistical Modeling - Data Readiness & Architecture Review - AI/ML Solution Design (PoC → Production) - Executive Workshops & Technical Enablement - Business–Product–Engineering Alignment - Enterprise BI & Decision Systems - Python, SQL, ML Tooling
The Graduate Center, CUNY, PhD in Computer Science
AI/Machine Learning
May 1, 2000 – Present
National Taipei University of Business
Finance & Taxation
N/A – Present
The City College of New York
MS, Computer Science
N/A – Present
The City College of New York
BS, Computer Science
N/A – Present
Enterprise AI & Analytics Consultant | Generative AI & LLM Advisor
Independent Consultant
January 1, 2025 – Present
San Francisco Bay Area · Remote
SAP SuccessFactors
Senior Product Manager, Machine Learning | Data Scientist
January 1, 2015 – January 1, 2024
San Francisco Bay Area · On-site
SAP
Lead Software Engineer – Analytics & Decision Systems
January 1, 2007 – January 1, 2015
Palo Alto, California, United States · On-site
Jaspersoft
Senior Software Engineer – Enterprise BI Platform
January 1, 2006 – January 1, 2007
San Francisco Bay Area · On-site
IBM, Bank of America, NativeMinds, Black Pearl, Apex
Earlier Career — Engineering & AI Systems Roles
January 1, 1989 – January 1, 2006
United States · On-site
GENERATIVE AI for NATURAL LANGUAGE PROCESSING PROGRAM
Great Learning
June 24, 2026 – Present
DATA SCIENCE AND MACHINE LEARNING: MAKING DATA-DRIVEN DECISIONS BY MIT IDSS
MIT Institute for Data, Systems, and Society (IDSS)
June 24, 2026 – Present
BUSINESS INTELLIGENCE and DATA WAREHOUSING
UC Berkeley Extension
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse background spanning enterprise software, AI systems, and financial systems, indicating adaptability. Their experience in advising enterprises on AI adoption and working on initiatives like pay equity suggests a focus on impactful, business-aligned solutions. The breadth of experience from early career engineering to senior product management and consulting roles demonstrates a continuous learning mindset and ability to adapt to evolving technological landscapes. However, the target role of 'Data Analyst' might be a step down from their extensive senior/lead/consulting experience, potentially leading to a mismatch in expectations or scope.
Soft Skills & Operational Fit
The candidate's experience as an Independent Consultant and Senior Product Manager at SAP SuccessFactors suggests strong leadership, cross-functional collaboration, and business acumen. Their role in securing executive sponsorship and translating business objectives into ML workflows indicates strong communication and strategic thinking. The long tenure at SAP also points to operational stability and ability to work within large enterprise environments.