Leo Jiang

Product Manager with 8 years translating operational and business requirements into structured workflows and delivery execution across complex enterprise platforms, including 3 years leading product for an AI-enabled simulation platform used by enterprise mining operations. Experienced working alongside engineering, data science, QA, and operations teams across the full SDLC, from requirements definition and workflow modelling through UAT, release coordination, and delivery optimization. Strong background reducing ambiguity, improving delivery flow, and translating complex technical constraints into clear, executable work.

Product Manager at Stream Systems Ltd. (2023-03 – 2026-03) Cloud-based AI simulation platform for enterprise mining operations

• Platform ownership: Led end-to-end product for an AI-enabled simulation platform that ran 2,000 to 20,000+ simulation scenarios per analysis, helping mine operators model equipment performance, identify production constraints, and evaluate operational trade-offs before committing to decisions in the field.

• Requirements and stories: Translated operational objectives and data science outputs into structured user stories, acceptance criteria, workflow definitions, and delivery-ready requirements across 7 to 10 concurrent initiatives per quarter. Sat in on technical design sessions to understand system constraints before writing requirements, which reduced clarification cycles during development.

• Release lifecycle analysis: Identified recurring bottlenecks in the delivery pipeline including unclear story definitions at intake, late-breaking scope changes, and misaligned acceptance criteria between QA and engineering. Introduced intake checklists, definition-of-ready standards, and a story review step before sprint start that reduced mid-sprint rework and improved release predictability quarter over quarter.

• Backlog and delivery flow: Joined a team with no PM process and 2,000+ unstructured tickets. Built prioritization frameworks, intake standards, and requirements templates from scratch that cut the backlog to under 100 well-defined items within the first quarter and gave the team a consistent way to evaluate new work.

• Scrum facilitation: Ran sprint planning, backlog refinement, dependency tracking, and retrospectives across engineering, data science, and QA. Reported delivery health, risks, milestone status, and workflow blockers to senior stakeholders each quarter.

• AI platform collaboration: Worked directly with data science and engineering teams to define model behaviour, validation thresholds, workflow reliability expectations, and how simulation outputs should be reviewed and interpreted by operational users before decisions were made. This included evaluating edge cases, acceptable confidence levels, and how to surface uncertainty without overwhelming users.

• Enterprise validation: Led beta programs with 5 enterprise customers including Rio Tinto, Suncor, Teck, Vale, and Roy Hill, validating workflows with planning and operations leads before general availability.

• Platform scope: Owned the roadmap for a mission-critical platform that dispatchers, maintenance crews, and field operators used in real time to track and allocate heavy equipment across active mine sites, spanning 15+ applications and 100+ enterprise deployments globally.

• Requirements from the field: Travelled to active mine sites to observe dispatcher and field workflows firsthand. Translated what was seen into structured workflows, system logic, decision rules, and platform requirements that engineering teams could build from, including the business rules and approval steps governing how the system responded in time-sensitive situations.

• Release lifecycle: Analyzed the release lifecycle across 4 agile teams and identified key bottlenecks including cross-team dependency gaps, inconsistent story definitions, and late UAT discovery. Introduced a shared dependency tracking process and story readiness review that improved delivery predictability across 8 releases per year.

• Multi-team delivery: Directed delivery across 4 agile engineering teams of 20+ engineers including an outsourced team in India, coordinating release planning, dependency management, milestone sequencing, and UAT across concurrent workstreams.

• Requirements standards: Authored user stories, acceptance criteria, and workflow definitions across all 4 teams. Introduced requirements templates and review practices that reduced ambiguity, defect leakage, and rework over time, with measurable improvement in development predictability.

• Stakeholder communication: Delivered roadmap updates, release risk summaries, and dependency reports to senior leadership each quarter. Mentored incoming Product Owners and standardized PM practices across the product group.

• Backlog reduction: Reduced the backlog from 4,000+ to under 500 tickets in 6 months through structured prioritization across 4 agile teams, cutting low-value work and aligning remaining items to measurable operational outcomes.

• Story writing and UAT: Wrote user stories and acceptance criteria, facilitated sprint planning, reviews, and retrospectives, coordinated UAT across teams, and led product demos to keep stakeholders aligned on what was being built and why.

• Cross-team alignment: Served as PO lead across concurrent workstreams, coordinating implementation decisions and feature releases across multiple teams including an outsourced team in India. Onboarded and coached new Product Owners on backlog management and story definition practices.

• Quality and delivery: Partnered with QA and support to incorporate production issues into the backlog and tighten acceptance criteria over time, reducing defect leakage across releases.

• Bachelor of Applied Science in Systems Engineering – Simon Fraser University (2007 – 2012)

• Product Strategy – Kellogg School of Management

• Certified Scrum Product Owner (CPSO) - Scrum Alliance

• Certified Scrum Master (CSM) - Scrum Alliance