Resume

Built 0→1 AI doc-intelligence platform; reduced decision cycle time 60%

• Launched a 0→1 AI document intelligence platform that automated high-stakes decision workflows across 3 business lines, reducing end-to-end cycle time by 60% and saving ~4,200 analyst hours annually.
• Built and defended a product vision and phased roadmap under heavy governance constraints, securing $1M in incremental funding by tying every milestone to measurable risk-reduction and efficiency outcomes.
• Co-designed an explainable ML decisioning layer with data science and governance teams, implementing real-time feedback loops and model monitoring that maintained 97%+ prediction reliability post-launch.
• Owned adoption OKRs across 3 LOBs; drove MAU up 40% through instrumentation, enablement playbooks, and targeted lifecycle campaigns that doubled 30-day active usage.
• Redesigned onboarding and in-app engagement journeys using segmentation and behavioural nudges, lifting feature engagement by 30% and reducing onboarding drop-off by 15% via A/B tested flows.
• Led end-to-end discovery and delivery: ran 25+ VOC sessions, authored PRDs with API contracts, and drove cross-functional alignment across engineering, UX, data science, and compliance.

Shipped real-time ML decisioning platform serving 1M+ users

• Delivered a real-time ML-powered decisioning platform unifying data science, UX, and governance inputs, serving 1M+ users with sub-500ms latency and 15% improvement in detection accuracy.
• Integrated external behavioural and financial signals into decision workflows, increasing approval rates by 22% while simultaneously reducing risk exposure by 9%.
• Led 15+ A/B experiments across onboarding, dashboards, and notification flows, improving user engagement by 18%, conversion by 18%, and reducing churn by 12%.
• Modernized mission-critical transaction flows to meet evolving compliance standards, delivering full regulatory alignment with zero disruption to daily processing volumes.
• Revamped API documentation and sandbox environments, accelerating partner integrations by 40% and reducing developer onboarding time from 3 weeks to under 1 week.
• Defined and shipped a KPI monitoring framework with real-time dashboards tracking SLAs, model performance, and business outcomes across all decision flows.

Migrated 3M+ accounts to cloud; achieved 99.9% uptime

• Led the migration of legacy billing infrastructure for 3M+ subscriber accounts to a cloud-native platform, achieving 99.8% billing accuracy, 99.9% uptime, and reducing manual adjustments by 70%.
• Drove reliability and scalability improvements that enabled the platform to handle 2× concurrent load during peak billing cycles without degradation.
• Revamped CRM-billing API integrations and developer onboarding flows, reducing integration time by 40% and cutting support tickets by 25%.
• Launched a self-serve billing portal that improved NPS by +14 points and reduced inbound support volume by 25% within 3 months of launch.
• Shipped in-app upgrade nudges and contextual prompts that lifted plan upgrade conversion by 10%; ran design sprints delivering 3 pilot-ready features in 2 months.

Built real-time marketing dashboards; lifted CTR 12%

• Built real-time marketing insights dashboards that enabled personalized campaign targeting across 4 channels, increasing CTR by 12% and contributing to a 6% lift in MRR.
• Architected a centralized data lake enabling self-serve analytics for 5 cross-functional teams, reducing ad-hoc data request turnaround from 5 days to under 4 hours.
• Diagnosed funnel bottlenecks using cohort and drop-off analysis; redesigned the signup flow improving conversion by 8% and reducing time-to-activation by 20%.

Seneca College — Toronto, ON

Conestoga College — Kitchener, ON

SRM University — Chennai, India