Rishi Yadav
AI • ML • Data Engineering LeaderTransforming Enterprises Through AI-ML & GEN AI Research and Automation
AI/ML data scientist and innovation lead with over 23 years of experience in AI/ML product development, data engineering, and research leveraging ML, DL, NLP and LLMs. Have led several teams developing innovative solutions to complex challenges faced by clients impacting all enterprise functions across Sales, Marketing, Pricing, Operations and IT.
High-accuracy SIP churn prediction lifted retention rates from 60% to 75% in the first 12 months
Achieved 94% model accuracy on sustainability twin predictions for a global bank, ensuring confident emissions pathway decisions
Agentic SDLC automation cutting engineering effort by 30-50% while maintaining quality and guardrails
AI-ML Tech and Domain Architect
Key Highlights of Professional Career
(2001 - Present)
- Senior Data Scientist with expertise in Artificial Intelligence, Reinforcement Learning, Machine Learning, Deep Learning and Advanced Simulation Techniques and hands-on experience on important ML frameworks (Scikit-Learn, Keras, PyTorch and TensorFlow)
- Previously Head of Product Engineering for TwinX™ which is an AI-ML Enterprise Digital Twin Platform Offering by TCS, where I helped expand AI Simulation products to new domains (banking, transportation, retail, healthcare)
- Led enterprise transformation projects in Digital Transformation, Sales And Marketing, Analytics and Business Intelligence, which resulted in strategic gains and operational efficiencies for global clients
- Implemented Automation of Business and IT Processes by leveraging GEN AI and Agentic AI frameworks (LangChain, LangGraph, LangSmith) along with automation tools and platforms (Zapier, n8n, TCS AI WinsdonNext)
- Big Data analytics and Data Engineering experience on cloud platforms (Google GCP, Amazon AWS, Microsoft Azure, Snowflake) and BI platforms (SAS, Tableau, Power BI)
- Indepth BFSI domain and functional experience in solving complex analytical problems for global clients across Investment Banking, Retail Banking, Wealth Management and Insurance
Featured Case
Autonomous SDLC Agents for Global Insurer
Streamlining Software Development with Agentic AI
“We cut our release cycle nearly in half within three quarters. The agentic workflow changes stuck because they respected our guardrails.”
— VP Engineering, Global Insurer (anonymized)
Companies Impacted
Tata Consultancy Services
TwinX • AI Engineering
Franklin Templeton
Growth Analytics • Simulation
Nippon Life India AM
Predictive Retention
Capgemini
Transformation Delivery
Infosys
Enterprise Programs
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Education & Credentials
Formal engineering, advanced machine learning specialization, and business leadership education shaping a balanced technical–commercial perspective.
IIT Kanpur
B.Tech
- Strong grounding in core engineering & computational thinking
- Foundation in algorithms, systems, and problem decomposition
IIT Kharagpur
Diploma in Machine Learning
- Applied machine learning & model evaluation practice
- Deployment rigor: performance, drift & responsible use considerations
ISB Hyderabad
MBA
- Strategic leadership & technology commercialization
- Financial modeling & value articulation for AI investments
Brand marks belong to their respective owners.
Case Studies
Practitioner-authored programs with measured impact. Read the narrative and the numbers.
Autonomous SDLC Agents for Global Insurer
CaseStreamlining Software Development with Agentic AI
SIP Churn Prevention ML Model
CaseProtecting INR 1000 Cr Through Predictive Analytics
Sustainability Digital Twin: Layered Optimization for a Global Bank
CaseAward-winning architecture forecasting emission pathways and investment trade-offs across six infrastructure layers.
Featured Article
Latest insights on AI transformation and enterprise implementation.
AI in Finance: From Pilots to Platforms
Explore how financial institutions are moving beyond AI pilots to build robust, scalable platforms that drive real business value. This comprehensive guide covers the journey from experimentation to enterprise-wide AI implementation.