Ying-Jeanne WANG

About Me

I'm currently General Manager at Amazi Moto Rwanda, an electric motorcycle financing and battery-as-a-service startup in Kigali, where I lead operations optimization and strategic planning. Prior to this, I spent over a decade as a senior engineer at companies like Grafana Labs and Amadeus IT, where I led complex technical initiatives including enterprise-scale migrations affecting 1000+ enterprise customers and served as Scrum Master for cross-functional teams.

My background combines deep technical expertise in distributed systems with hands-on project management experience. I've led high-complexity projects like the Mimir billing infrastructure and FedRAMP security compliance, while also developing skills in operations research, financial modeling, and strategic problem-solving. This unique blend of technical depth and operational leadership, particularly in emerging markets, positions me well for strategy and operations consulting roles.

What sets me apart is my proven ability to rapidly master diverse technical and business domains. My journey spans automotive systems engineering (infotainment HMI, signal processing, factory process optimization) at PSA and Renault, to distributed cloud infrastructure at Grafana Labs, to now managing real-world operations in Rwanda. Currently pursuing an MSBA (Master of Science in Business Analytics) at NUS Business School with focus on blockchain, machine learning, and operations research, I continuously challenge myself to expand my skillset and stay at the forefront of emerging technologies and analytical methodologies. Business fluent in English, French, and Chinese, I bring cross-cultural communication skills essential for global consulting engagements.

Business & Strategy

Project Management Certified Scrum Master ITIL Certified Operations Research Financial Modeling Process Optimization Emerging Markets

Technical

Distributed Systems Applied AI/ML Data Analysis Blockchain Go, Python, C++ SQL, NoSQL, Object Storage Docker Cloud (AWS/GCP/K8s)

Industry

E-mobility Clean Energy Automotive Systems Travel Tech Hospitality Observability

Languages

English (Business Fluent) French (Business Fluent) Chinese (Native) Spanish (Basic)

Experience

General Manager

Amazi Group(Electric motorcycle financing and battery-as-a-service startup) Apr 2025 - Dec 2025

Leading end-to-end operations including vendor procurement and selection, software system integration, and building local technical talent through strategic hiring. Managing import operations, tax compliance review, financial reporting, and global budget allocation. Developed financial modeling dashboards identifying key business drivers for strategic decision-making and investor communications.

Senior Software Engineer

Grafana Labs (Open-source observability platform, 20M+ users globally) Dec 2020 - Apr 2025

Grafana Platform (Backend for User & Dev Experience): Focused on enhancing user and developer experience by implementing "Dashboard as Code" (CUE) and delivering critical community features like Nested Folders. Led backend refactoring (removing legacy xorm) and the Logger library migration, significantly simplifying the architecture to facilitate open-source contributions and improve security.

Mimir (Distributed Systems): Engineered core components for Grafana Mimir, a highly scalable distributed time-series database. Architected the billing infrastructure (Cost Attribution) to provide detailed billing breakdowns and insights for enterprise clients. Enhanced system reliability and ingestion paths by implementing intelligent rate limiting and retry logic. Drove the Patch All Things initiative (Tooling and Distroless migration, CI/CD), reducing vulnerabilities by 40% for FedRAMP compliance.

Implementation Project Leader / Scrum Master / Senior Engineer

Amadeus IT (Leading global travel technology platform for airlines and hotels) Jan 2016 - Dec 2020

Implementation Project Leader: Modernized the implementation workflow by replacing legacy manual VBA scripts with a modern Python automation pipeline. Automated the entire activation process (SQL generation, testing, SMTP email integration, JIRA/Confluence updates, Jenkins workflows), reducing time cost by 90% and achieving zero human interaction. Developed Grafana dashboards for workload visibility. This initiative permanently transformed the team's hiring strategy to focus on Python talent. Went the extra mile to unblock implementations by investigating logs and coordinating with different dev teams. Completed comprehensive hospitality business training and served as a customer-facing technical expert.

Scrum Master: Mentored a cross-functional team of 8 (5 Developers, 2 BAs, 1 QA). Facilitated all Scrum ceremonies (Planning, Sizing, Demo and Retro) and led feature delivery while training junior engineers on development best practices.

Senior Software Engineer: As an early developer, built the high-availability distributed booking system for IHG (InterContinental Hotels Group) from scratch on C++11 within a complex microservices architecture, and using SQL & Couchbase as databases. Deployed with docker container on OpenShift and in-house cloud environments. Implemented critical features including Group Reservations, Loyalty Programs, Allowances, and PMS integrations.

Technical Consultant / Software Engineer

PSA Group (Fortune 500 Automotive Company - Peugeot and Citroën) Dec 2013 - Oct 2015

Developed a dashboard simulator (C++/Qt) to serve as a visual "golden standard" for suppliers, eliminating ambiguity in written specifications. This approach drastically reduced miscommunication and development iterations with embedded system vendors. Empowered the specification team to adopt this visual-first methodology, streamlining the entire supply chain communication process.

Signal Processing Engineer Intern

Renault Group (Fortune 500 Automotive Company) Apr 2013 - Oct 2013

Developed an automated safety diagnosis system for Parking Brake Assist to detect critical installation errors (e.g., mismatched components) on the factory line. Built mathematical models of electromechanical parts (DC motors, brake discs) to derive system transfer functions from electrical signal inputs. Implemented Bayesian decision algorithms to accurately identify brake types, ensuring 100% compliance before vehicle release.

Signal Processing Research Intern

CNRS (Centre National de la Recherche Scientifique) June 2012 - Aug 2012

Developed a MATLAB-based reconstruction pipeline to validate experimental data. Implemented Filtered Back Projection (FBP) and numeric filters, providing the research team with a reliable tool to transform raw sinogram inputs into visualizable images for analysis.

Portfolio

Rwanda Moto Battery Swap Optimization

Challenge: Optimize battery swap station locations and inventory for electric motorcycle financing and battery-as-a-service startup in Kigali, balancing driver downtime against infrastructure costs.

Approach: Building predictive models using operational data to forecast battery demand and project inventory requirements. Developing operations research optimization framework for battery swapping station placement and capacity planning.

Status: Project in progress. Currently gathering operational data. Next phases: demand forecasting, MILP optimization for station location and inventory allocation, eventually make next phase battery procurement planning.

Operations Research Optimization Demand Forecasting Inventory Management

Cost Attribution Billing Infrastructure

Challenge: Design scalable billing system for Grafana Mimir to track high-volume metrics ingestion and attribute costs to enterprise customers across teams and projects.

Approach: Architected real-time usage metering system handling billions of data points daily. Designed cost attribution model balancing accuracy and efficiency.

Impact: Infrastructure handles 10M+ metrics/second with full accuracy. Enabled transparent usage-based pricing, improving customer trust and revenue predictability. View official documentation →

System Design Billing Scalability Production Performance Optimization

FedRAMP Security Compliance Initiative

Challenge: Achieve FedRAMP compliance for Grafana Cloud to serve government and enterprise clients, requiring vulnerability reduction and meeting 30-day patch remediation timelines.

Approach: Piloted Patch All Things initiative. Designed and implemented: dependency vendor selection, Distroless migration, CI/CD improvements, and security monitoring dashboards/alerts.

Impact: Reduced vulnerabilities by 40% while establishing automated patching workflows meeting FedRAMP timelines. Enabled Grafana FedRAMP certification for critical enterprise clients. Framework adopted company-wide and shared with the Cloud Native community as a best practice.

Security & Compliance FedRAMP DevSecOps CI/CD Thought Leadership

Academic Projects

Blockchain-Based ML Prediction Transparency Platform

Challenge: Demonstrate blockchain's value beyond cryptocurrency through a transparent ML prediction system for financial markets.

Approach: Developed ML model for Bitcoin price prediction with automated pipeline and smart contract integration to store predictions immutably on blockchain. Designed backend architecture and data pipeline (frontend assisted by AI tools).

Impact: Live platform showcases blockchain for trust and transparency in ML systems. View live demo →

Applied ML Blockchain Pipeline Engineering Backend Design Smart Contracts Web3

Explainable Credit Default Prediction

Challenge: Human review for small loans is costly and slow, making automation financially necessary. The solution must optimize business cash flow over pure accuracy, while meeting legal transparency requirements.

Approach: Benchmarked multiple ML models for performance. Implemented SHAP for selected black-box LightGBM model to ensure legal compliance and explainability, facilitating a transparent dashboard for loan officer review.

Impact: Achieved 207% increase in Net Cash Flow vs standard F1 optimization. Provides loan officers with an interactive tool to visually explain how a decision is made. View live demo →

Explainable AI (XAI) Finance Risk Management Legal Compliance

TSP Integrality Gap Visualizer

Challenge: Visualize and analyze the "integrality gap" in the Traveling Salesperson Problem (TSP) to understand algorithm performance across different city structures.

Approach: Built an interactive Python-based tool to generate diverse city instances and run comparative algorithms.

Impact: Provides visual intuition for complex Operations Research concepts, aiding in the analysis of algorithmic efficiency. View live demo →

Operations Research Optimization Python Visualization

Hi, I'm Ying-Jeanne WANG 👋