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Head of Artificial Intelligence
Seasoned AI & Data Science leader with 15+ years in the field. Last 2 years spent building end-user products on LLMs and unstructured data. Currently leading: AI org design and growth: hiring senior ICs and managers, defining career paths, and shaping the research / engineering / product — Product strategy for Agentic AI use cases — copilots, conversational interfaces, document intelligence, semantic search, agentic workflows — owned from problem framing through GA and post-launch iteration — Technical strategy: model selection, build-vs-buy, post-training investment, infra and orchestration choices, and the evaluation philosophy— Cross-functional partnership with product, design, GTM, legal, and the executive team — translating model capability into roadmap, and roadmap into measurable customer and business outcomes Currently Building: Retrieval systems over unstructured corpora (PDFs, transcripts, emails, code, multimodal): parsing, chunking, embeddings, hybrid search, reranking, grounding — Agentic systems with tool use, planning, memory, and the guardrails that make them safe in production — Post-training programs: SFT, preference tuning, distillation, and structured-output reliability for domain-specific behavior — Evaluation infrastructure: offline benchmarks, LLM-as-judge, regression suites, and online experimentation — the loop that turns demos into dependable products — Production inference at scale: latency, cost, observability, and failure-mode containment How I operate: Strong opinions on the unglamorous parts — data quality, eval rigor, error taxonomies, and the gap between a working demo and a dependable product — and I push the org to invest there. Keeping the loop tight between research, engineering, and customer-facing reality, and trust ICs with real scope. Equally comfortable in a code review, a roadmap debate, or a board u
Indian Institute of Technology, Delhi
B.Tech, Engineering Physics
January 1, 2006 – January 1, 2010
Spice Money
EVP & Head of Artificial Intelligence
January 1, 2026 – Present
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Executive Vice President | Data Science & ML
September 1, 2024 – Present
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July 1, 2021 – October 1, 2023
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February 1, 2019 – July 1, 2021
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May 1, 2018 – January 1, 2019
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CoinTribe Technologies
Principal Data Scientist
March 1, 2016 – May 1, 2018
Gurugram, Haryana, India
CoinTribe Technologies
Lead Data Scientist
July 1, 2015 – March 1, 2016
Gurugram, Haryana, India
Machineparty, Inc.
Data Scientist - Consultant
January 1, 2015 – June 1, 2015
San Francisco Bay Area
Snapdeal
Lead Data Scientist
April 1, 2014 – January 1, 2015
Snapdeal
Data Scientist (Klickpay)
October 1, 2013 – April 1, 2014
Ibibo Group
Data Scientist
October 1, 2012 – October 1, 2013
Gurugram, Haryana, India
Parametric Technology Corp.
Data Analyst
July 1, 2011 – July 1, 2012
Gurugram, Haryana, India
BIAS - Bremer Institut für angewandte Strahltechnik GmbH
Staff Scientist
May 1, 2010 – August 1, 2010
Greater Bremen Area
XLIM
Guest Scientist
May 1, 2009 – July 1, 2009
Greater Limoges Area
Cultural Fit Analysis
The candidate has a long and consistent career path within data science and AI, primarily in fintech and e-commerce, demonstrating stability and deep domain expertise. Their experience spans various aspects of data science, from hands-on model development to strategic leadership, indicating a broad skill set. However, the target role of 'Data Analyst' is considerably junior to their extensive experience as an EVP/SVP/Head of AI/Data Science. This significant discrepancy raises questions about cultural fit for a role that might not fully leverage their leadership and strategic capabilities, potentially leading to disengagement or overqualification. While their project diversity within data science is good, the role alignment is a concern.
Soft Skills & Operational Fit
The candidate's career progression indicates strong leadership, strategic thinking, and the ability to build and manage technical teams. Their descriptions highlight an AI-first approach and focus on developing custom solutions, suggesting a proactive and innovative operational fit. The emphasis on 'Billion Bharat customers' and 'South East Asian market' implies a customer-centric and adaptable mindset. However, the target role is 'Data Analyst' which is a significant step down from their current and past leadership roles, suggesting a potential mismatch in operational expectations or a desire for a more hands-on, individual contributor role.