Why financial AI
built by someone who lived it
works differently.
In 2017, I joined State Street Global Advisory as a Reconciliation Analyst. Every day: Bloomberg Terminal, Refinitiv Eikon, SmartStream TLM. Reconciling 100+ managed pension fund portfolios — equities, derivatives, FX, post-trade settlement, corporate actions. The grinding, precise, high-stakes work of institutional asset management.
Most people would see that as a detour before a "real" tech career. I see it as the most important thing I ever did. Because when I crossed over to data science at LSEG in 2019, I didn't just bring Python and statistics — I brought an intimate understanding of the data I was now being asked to automate.
I knew why Korean regulatory filings were structured the way they were. I knew what made a broker report ambiguous. I knew which edge cases would break a production system in the third month, not the third day. That knowledge is not in any dataset. You get it by living inside the domain.
Nine years in, £600K+ delivered, 55 FTEs automated across global financial workflows — I'm looking for the next stage: Singapore's fintech and financial services ecosystem.
My unfair advantage
Domain-first
I understand the financial instruments, workflows, and failure modes of the systems I'm automating — before a single line of code.
Commercially accurate
My AI systems are optimised for business outcomes, not benchmark scores. £600K+ in delivered value is the only benchmark that matters.
Full-stack AI
From data extraction pipelines to agentic orchestration to LLM fine-tuning to LLMOps. I ship systems end-to-end.
Three chapters
Reconciliation Analyst
Domain FoundationState Street Global Advisory · Bangalore · Feb 2017 – Oct 2019
Learning the language of financial markets.
- Reconciled 100+ managed pension fund portfolios — equities, derivatives, FX — using Bloomberg Terminal, Refinitiv Eikon, and SmartStream TLM
- Managed daily multi-currency position/cash reconciliation and corporate actions (M&A, dividends, tender offers)
- Built PowerBI exception-trend dashboard for Portfolio Managers — the first AI-adjacent work, directly driven by frontline data pain
- Deep institutional asset management expertise: cross-custodian workflows, post-trade settlement, regulatory reporting — this became the domain foundation for everything at LSEG
Data Scientist
Applied MLLondon Stock Exchange Group · Bangalore · Nov 2019 – Oct 2022
Turning domain knowledge into production ML pipelines.
- Korean regulatory filing extraction: 85%+ hit rate, £250K+ savings, 5 FTE reduction — processing cut from 15 days to 40 minutes across 130K+ documents
- Hybrid ML + rule-based ingestion (cosine similarity, two-stage classification) across CA, IN, US, AU — saved 3 FTEs, cut out-of-scope data by 50%
- Two-stage document intelligence pipeline (Azure Layout Model + Python rules) — expanded image-based document coverage from 0% to 64%, eliminating 5 FTEs
Senior Data Scientist
GenAI LeadershipLondon Stock Exchange Group · Bangalore · Nov 2022 – Present
Leading the shift from ML to GenAI — with financial domain embedded from the start.
- Built GenAI financial data extraction pipeline (meta-prompting, PydanticAI) — £350K+ savings and 50 FTE reduction
- Developed context-aware RAG Answer Engine — source-referenced responses, session memory, optimised prompt design for analyst productivity
- Led multi-agent AI PoC for financial document intelligence — earned regional executive endorsement
- Mentored data scientists; translated financial domain knowledge into scalable AI pipelines
Technical skills
PG Diploma, Finance & Operations
ISME, Bangalore
2015 – 2017
B.Tech, Mechanical Engineering
Silicon Institute of Technology, Odisha
2010 – 2014
PG Programme in Data Science
INSOFE / Carnegie Mellon University
Machine Learning in Production
Andrew Ng · Coursera
Complete MCP Developer Guide
Udemy
Six Sigma Green Belt
KPMG
Open to opportunities
Seeking senior IC and lead roles in Singapore's fintech and financial services ecosystem. If you're building production AI in financial markets and want someone who actually understands both sides, let's talk.
abhilash.k.panda@gmail.com →