Open to opportunities

Abhinit Sen

@abhinitsen

Message

AI Product & Analytics leader building LLM and data-driven decision systems for growth.

India

Message

What I'm looking for

I’m looking to lead senior AI product and analytics work where I can own outcomes end-to-end—strategy, use-case prioritisation, pipelines, and adoption—building agentic/LLM-enabled decision systems with strong experimentation and governance.

I’m an AI Product & Analytics leader with 14+ years delivering data-driven systems, analytics platforms, and AI-enabled decision infrastructure across financial services and enterprise growth. I own product and delivery end-to-end—from problem scoping and use-case prioritisation to pipeline deployment and stakeholder adoption—across 15+ client engagements, including scaling one platform from 0 to 75,000 users and driving 25% growth across a portfolio.

Right now, I’m running an independent AI Product & Analytics practice in Bengaluru while completing ISB AMPBA, applying agentic AI frameworks, LLM evaluation, and data engineering directly to live client work. I’ve designed LLM-assisted decision workflows that compress the insight-to-action cycle from 3 days to 4 hours, built ML-driven behavioral decision frameworks, and productised experimentation with rigorous A/B testing methodology so teams can optimise independently.

Experience

Work history, roles, and key accomplishments

Current

AI Product & Analytics Lead

Current

Independent Consulting Practice

Oct 2021 - Present (4 years 8 months)

Owned end-to-end delivery for AI-enabled growth and decision systems across 15+ brand clients, scaling one platform from 0 to 75,000 users and driving 25% portfolio growth. Built LLM-assisted decision workflows and behavioral analytics/ML frameworks, compressing insight-to-action from 3 days to 4 hours and improving engagement by 40% with conversion rising from 3.1% to 8.4% in 90 days.

LLM Evaluation Behavioral Analytics Python SQL

Lead IT Business Analyst

Saxo Bank

Jan 2021 - Oct 2021 (9 months)

Identified and remediated a regulatory coverage gap, expanding CRS reporting from 3 to 6 jurisdictions, growing reportable accounts from 5,000 to 12,000, and reducing compliance gaps by 30% in six months. Designed analytics pipelines for 10,000+ monthly transactions, automating validation workflows that saved 10+ hours per week and improved discrepancy detection speed by 15%.

Regulatory Reporting Compliance Analytics SQL Stakeholder Management

Product Owner / Senior Analyst

Wells Fargo

Jun 2018 - Jan 2021 (2 years 7 months)

Owned an onboarding API serving 5,000+ users, defined success criteria and backlog, and delivered workflow improvements that increased onboarding completion by 30% while reducing the compliance backlog within six weeks. Built a behavioral graph model for Customer Due Diligence to reduce manual compliance checks by 30% and improve early defect detection by 80%.

Product Ownership API Product Management Customer Due Diligence Compliance Analytics SQL

Business Analyst

Publicis Sapient

Oct 2011 - Jun 2018 (6 years 8 months)

Designed and rebuilt MiFID II and OTC transaction reporting/data processing across asset classes, reducing batch processing from 12 hours to 4 hours and reporting latency from 15 seconds to under 5 seconds. Standardized data mapping and validation workflows, improving compliance rates from 30% to 60%+ through robust data integrity controls handling 10,000+ daily transactions.

MiFID II Data Validation Data Integrity Batch Processing SQL Compliance Analytics

Education

Degrees, certifications, and relevant coursework

Indian School of Business (ISB)

AMPBA, Business Analytics & AI

Activities and societies: Applied agentic AI frameworks, RAG architectures, LLM evaluation methodology, ML pipelines, and data engineering to live client engagements; examples include LLM evaluation and data engineering improvements.

Expected to complete the AMPBA program in Business Analytics & AI (Oct 2026) while applying coursework directly to live client work. Coursework includes agentic AI frameworks, RAG, LLM evaluation, ML pipelines, and data engineering at scale.