Rajesh Kumar Singh

About Rajesh Kumar Singh

SUMMARY:Thought leader enabling Copilot (GenAI & Agentic AI) and Multimodal Agents (voice, text, image) infused experiences into products. Drive business strategies through AI/LLMs/Agents/Machine Learning @ Scale, Data Science, Predictive and Advanced Analytics (Insights) by leveraging omni-channels (user/device telemetry, unstructured text - chat/customer verbatim, visual - images and speech - conversation) for PRODUCT growth. Strategic thinker with Global perspective and International work experience. Led, Built and Mentored High Performance Teams of Applied Data Scientists, ML Engineers and Data analysts at Microsoft, IBM and Chase. Also, worked at GE & USEPA. Experience spans key positions in LLM, Copilot Synthetic data, Agentic AI, Machine Learning, and Data Science domains.LEADERSHIP: Strategic partnerships; Cross-Groups/Orgs Leadership; Built high performance global teams of Machine learning, AI Applied & Data scientists and engineers; Led customer experiences powered by LLMs & AI for Business Stakeholders & SLT; Led Responsible AI initiatives for customer care apps; EBC speaker on AI at Microsoft; Pacific Northwest Analytics Leadership Board; Served on International Journals reviewers committee, Machine Learning & Data Science Conferences & Fireside chat forums.TECHNICAL:Deep knowledge and understanding of LLM / ML - Foundational models, LLM response quality, Synthetic data, RAGs, Prompt optimization, Conversational AI (NLP/U), Virtual agent/bot; Personalization - RL; Deep learning - RNN, BP, FFP, KB; Recommendation systems - next best action; Causal Inferencing - DML, DECI; Time Series - MC, ARIMA; Clustering; Regression; Classification - supervised and unsupervised; Simulation - Optimization; Media Mix modeling); Longitudinal cohort studies; Survey design and analysis; Experimentation - OEC, Guardrail metrics. Collaborated with third party industry partners (comScore, Compete, Nielsen, Steam, Flurry) for Compete SWOT analytics, Primary/Secondary research.ISVs/DOMAINS: LLMs, Copilot - Microsoft 365 products; Customer Care Support/Self-help/Field Services/IoT/Unified Routing); Azure Cloud & AI services; Computer Vision (Object/Parts detection); Resource & Optimization (Scheduling, Optimizer, MC); Supply Chain (Intelligent Inventory/Order management, Device returns sourcing & logistics management - Surface device genealogy, HoloLens patterns recognition); Gaming (Forza, Halo, etc.); Search (Bing); Social media (MSN portal services, Community forums); CRM (Dynamics).

Experience

1. Principal Ai Leader

   Microsoft

   Nov 2020 — Present · Seattle, WA, US

   Currently Leading Multimodal Agents Quality (Agent voice recognition, Agent reasoning and Agent Response) efforts for Microsoft D365 autonomous Contact Centers across Voice ASR, S2S, TTS, S2T, and Visual modalities as Principal AI Applied Science Manager.In the past owned Generative AI (Copilot) & Personalization initiatives (Prompt intent classification, Synthetic data, Conversational multi-turn SAT for Chat, Agents and Canvas scenarios - Bizchat, Word, Excel, PowerPoint, Teams, Outlook)@Scale, Causal Inferencing and Customer Lifetime Value insights powered by LLM\'s foundational models augmented with SMLs, RAGs, RL and machine learning models for JTBD in-app business scenarios for M365 - WXP (E+D) product portfolio mapped to customer journey states (acquisition, conversion, engagement and revenue) at Microsoft as Principal ML Scientist leader.

Education

• GB Pant University, Nainital, India

  Engineering

• Purdue University Daniels School of Business

  MBA

• Purdue University

  MS, Computer Systems (Computer Science and Information systems)

• Purdue University

  PhD (Pattern recognition using Data Mining and Statistical techniques), Engineering

• McGill University

  MS, BioResource Engineering