AI | Product | Dev | Data | Finance
Skills
Product, AI, Tech, Data, Finance - some relevant skills I have gathered over the years
AI Stack
Tools, techniques, and governance for building and evaluating AI-native products.
Claude Code
Cursor
Lovable
Google AI Studio
n8n
Replit
RAG architecture
Agentic workflows
MCPs
Prompt engineering
Responsible AI frameworks
ROI & regulatory risk
GenAI use case prioritization
AI policy & governance
Product Management
Product skills gathered across professional experience, academic projects and personal initiatives
Product discovery
User research
PRDs
Market analysis
Competitive analysis
Pricing strategy
Cost-benefit analysis
Vendor evaluation
Roadmapping
Prioritization
A/B testing
Agile / SDLC
Stakeholder management
Change management
Executive presentation
Workshop facilitation
JIRA
Confluence
Asana
Notion
Miro
Figma
Visio
Technical Stack
The engineering layer for writing code and shipping products.
Python
Java
JavaScript (Vue.js)
MongoDB
Kafka
Distributed systems
REST APIs
Microsoft Azure
Docker
Git
Data Stack
Platforms, BI tools, and data governance practices from enterprise engagements at PwC
SQL (Oracle, MySQL)
R
Snowflake
Collibra
PowerBI
Tableau
Mixpanel
Amplitude
Data governance
Data quality
Master data management
Metadata management
Data pipelines
Data Privacy
Finance Stack
Financial data platforms, source systems, and regulatory domains from three years at PwC Tech Advisory.
S&P Capital IQ
Bloomberg Terminal
Chronograph
SAP
Oracle (upstream context)
Private equity portfolio monitoring
Banking data strategy
Regulatory reporting (BCBS, SEC Form PF, ESG, Anti-trust)