Work

Twelve years, one thread.

Every role has been a version of the same job: take messy, disconnected data and turn it into decisions people trust. Here's how that played out.

Career at a glance12+ years
201520172019202120232025
DellAB InBevAffineAccentureJPMorgan Chase
IndustriesBankingInsuranceFashion retailGamingManufacturingConsumer goodsJewellery e-commerceTechnology
032025 — now

Chapter 3

Enterprise AI at scale

At JPMorgan Chase I own the product side of the firm's AI and data tools for Analytics, Finance, Risk and Corporate Development. The flagship is a firm-wide knowledge graph with a GenAI layer on top: one set of trusted definitions, and a way for anyone to ask questions of it. Around it sit the tools that make data usable day to day — duplicate-work detection across teams, competitor tracking, news ingestion, and AI-generated company profiles.

40%+query accuracy gain
60%less SME dependency
50–70%faster knowledge-graph builds
What I learnedAt enterprise scale, trust is the product. Governance isn't overhead — it's the feature.
JPMorgan ChaseVice President — FAST TeamMay 2025 — Present
Projects from this chapter
022019 — 2025

Chapter 2

Consulting across industries

Six years at Affine and Accenture, taking data science into businesses that ran on very different problems — fashion, gaming, manufacturing, insurance, jewellery. I grew from building models to owning whole engagements: framing the problem with CXOs, setting the roadmap, and leading a team of 15+ data scientists to deliver it.

15+data scientists led
$2M+net business impact
~$1Mfrom one risk model
What I learnedA great model that nobody adopts is worth nothing. The roadmap is a people problem first.
AffineSenior Principal — Data ScienceDec 2021 — Mar 2025
Accenture ConsultingConsultant — Data ScienceApr 2021 — Dec 2021
AffineConsultant — Data ScienceNov 2019 — Apr 2021
Projects from this chapter
012015 — 2019

Chapter 1

Learning how the business works

I started at Dell running infrastructure projects, then moved into data science at AB InBev. That's where I learned that analysis only matters when someone owns the decision it feeds — so I built the business case to bring brand-cannibalization analytics in-house and put it directly in revenue managers' hands.

~$1Mprojected annual savings
25%better capacity utilisation
30%less system downtime
What I learnedStart from the decision, not the data.
AB InBevAssociate Data ScientistAug 2018 — Nov 2019
Dell TechnologiesSenior AnalystJan 2015 — Aug 2018
Projects from this chapter

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