Jobs in Canada

Environmental Control Analyst in Canada

453 active opportunities · Updated October 2026

Explore current environmental control analyst jobs across Canada. Filter by work mode, employment type, experience, department, date posted and distance.

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📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -73.4%
Quick readStrong listing-quality and freshness signals

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Sitting within the broader Safety & Customer Care team, Lyft's Customer Care Operations organization manages over 1.7 million monthly customer interactions and serves as the company's primary direct touchpoint with riders, drivers, and businesses — spanning frontline support across multiple customer segments, a global BPO workforce, and the central functions that enable them to operate at scale. The Director of Business Planning & Central Operations is a newly created role at the center of how Customer Care runs and grows. This leader will ensure the org is resourced and positioned for the future, and will own the functions that keep Customer Care financially disciplined and execution-ready. Reporting to the Senior Director of Customer Care Operations, they will lead five functions: Planning & Forecasting, Workforce Management, Readiness & Integration, Vendor Management, and Support Excellence. What You'll Do Business Planning & Strategy Partner with the Senior Director to drive H1 and H2 planning — translating annual objectives into operational plans, investment decisions, and resource models. Lead the investment brief process: sizing opportunities, articulating trade-offs, and building the business cases that secure resourcing for strategic priorities. Drive capacity planning, scenario modeling, and long-range forecasting to ensure the internal and external workforce scales efficiently alongside platform growth and AI adoption. Define and operationalize OKRs across the portfolio, then build the rhythms and infrastructure — scorecards, business reviews, and performance dashboards — that hold teams accountable and give leadership clear visibility into progress and outcomes. Growth & Integrations Lead operational readiness for major product launches, external partnerships, and

L
📍 San Francisco, CA· Full-time
✓ High-confidence listingCompany trend -73.4%
Quick readStrong listing-quality and freshness signals

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft is hiring an experienced, talented and energetic M&A lawyer to join our expanding Legal team. You will lead a broad range of corporate and transactional matters and provide effective, business-focused legal advice to stakeholders throughout Lyft. Our legal work is cutting edge and always evolving. Reporting into the VP, Deputy General Counsel, Corporate & Commercial, we are looking for an entrepreneurial, resourceful, and highly collaborative leader who can continuously assess and advise on legal issues using a creative and pragmatic approach. Responsibilities: Lead a wide range of corporate initiatives, including complex M&A and integrations, divestitures, strategic investments, joint ventures, domestic and international corporate structuring, capital markets transactions, financing matters, subsidiary management and other strategic corporate projects. Manage and mentor a high-performing in-house team of M&A legal professionals, fostering a culture of growth and execution excellence. Partner closely with Lyft’s Corporate Development team and Treasury team as well as advise company leadership and cross-functional stakeholders (e.g. people, accounting, tax, treasury, operations, etc.) on novel corporate legal issues, opportunities and risks of corporate transactions. Draft and negotiate NDAs, LOIs/term sheets and definitive transaction agreements. Shape, scale and improve our legal processes/playbooks that enable both legal and business functions to scale effectively. Assist other teams with projects on an as-needed basis. Experience: 10+ years of experience practicing corporate and securities law, with an emphasis on M&A and strategic transactions; experience at a top-tier law firm and in-house experience at a public company are both required. Degree from top-tier law s

L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -73.4%

From C$216K/yr

Quick readStrong listing-quality and freshness signals

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. On the Rider team, we are growing our team with people who want to enrich the lives of our community through technology. You'll collaborate with highly cross-functional teams such as Product, Design, Data science, and Analytics, as well as other organizations like Driver, Partners, and Marketplace, to deliver on that promise. As the Senior Engineering Manager for the Rider Loyalty, Partnerships, and Rider Pay (PLP) group, you will lead multiple managers and Staff ICs with end-to-end teams, consisting of iOS, Android, and Server, to make Riders into Members and to build a robust network of partners that our Riders love. It is your responsibility to sweat the details by being customer-obsessed with specific Rider needs and to build innovative product solutions to address them. Responsibilities: Set the technical vision and team strategy for the PLP group and communicate that downwards, with peers, and upwards with ELT Coach and guide an organization of managers and engineers in their people and technical development Collaborate with cross-functional stakeholders to deliver high business impact Work closely with the Lyft recruiting team to hire high-potential candidates from diverse backgrounds Experience: BS/MS or equivalent in Computer Engineering, Computer Science, or a related field, or relevant work experience 3+ years of experience managing engineering teams of 20+ members, including teams across iOS, Android, and Server platforms, as well as experience in managing managers Ability to thrive in a heavily cross-functional environment and drive projects to completion regardless of the organizational structure Passion for building scalable and extensible solutions that enable others and ensure a high-quality product Experience launching and supporting consumer-facing products at scale Strong technica

L
📍 San Francisco, CA· Full-time
✓ High-confidence listingCompany trend -73.4%
Quick readStrong listing-quality and freshness signals

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The People Technology stack has never been more capable, the differentiator now is the expertise to unlock it. . As a Senior Workday Engineer at Lyft, you'll be the technical cornerstone of our People Technology team, owning the design, development, and delivery of the integrations, custom applications, and AI solutions that the entire People function depends on. This role uniquely combines deep, demonstrable mastery across the full Workday technology stack with an AI-native engineering approach, enabling you to build solutions that don't just automate what exists today but fundamentally raise the bar for how People Technology delivers value. We're seeking a hands-on engineer who commands the full depth of the Workday ecosystem, from Studio and Core Connectors to Extend and Prism Analytics, and brings the technical judgment to architect solutions that scale with the business. You'll be the trusted technical owner of our People Technology platforms, partnering closely with HR, Payroll, Finance, and Benefits stakeholders to translate complex requirements into scalable, maintainable solutions that truly move the needle. With AI reshaping how People Technology teams operate, your expertise will be critical in actively identifying, building, and shipping AI-powered solutions that eliminate manual work, accelerate delivery, and push our teams from tactical execution to strategic impact. In this role, you'll integrate LLMs into HR workflows, build and maintain MCP servers that expose People systems data securely to AI agents, mentor junior engineers, and set the engineering standard for a team that is redefining what enterprise People Technology looks like. If you are a candidate who has the vision of what could be, who has the ability to cultivate relationships, and has a belief in driving impact, then you

RestAIGoRust
L
📍 San Francisco, CA· Full-time
✓ High-confidence listingCompany trend -73.4%
Quick readStrong listing-quality and freshness signals

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. We are building out Finance business operations to drive disciplined execution of both organic and inorganic initiatives, including M&A integration, strategic programs (AVs, Luxury), and other new product initiatives (NPIs). This is a strategy-to-execution role that requires strong judgment, cross-functional leadership, and the ability to drive outcomes in ambiguous, high-stakes environments. We are seeking a high-impact Finance BizOps leader to sit at the center of this effort, owning finance integration execution (in partnership with Lyft’s Corp Dev IMO), NPI financial readiness, and the intake/governance layer that connects Finance to the company’s most strategic initiatives. This role is the operating backbone for Finance – ensuring acquisitions integrate seamlessly, new products launch cleanly, and Finance work is prioritized with rigor and transparency. As the company scales, the volume and complexity of strategic initiatives—M&A, new products, and cross-functional programs—continues to increase. This role establishes a centralized operating model that ensures: Strategic initiatives are executed with discipline and completeness Finance is embedded early and effectively ensuring strong planning to execution across multiple teams to deliver strong customer and business results The organization scales without accumulating operational debt or technical debt Responsibilities: Strategic program Readiness Act as the central Finance lead for new product initiatives and large strategic programs Build strong working relationships with key product and business leaders and stay “in the know” on planned launches Partner with Finance SMEs, Product, Engineering, and GTM teams to ensure: Financial workflows and requirements are defined Systems, processes, and financ

L
📍 San Francisco, CA· Full-time
✓ High-confidence listingCompany trend -73.4%
Quick readStrong listing-quality and freshness signals

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. As an Engineering Manager on the Core Rider team, you will act as a critical technical leader in a highly visible area of the Rider Organization. Taking holistic ownership of our foundational systems and core rider functionality, you will be directly responsible for moving top-line business metrics and delivering a seamless rideshare experience. You will partner with multiple product managers, data scientists, and cross-functional teams to develop complex systems, define strategic roadmaps, scale the product and infrastructure that powers how millions of riders request and experience their rides every day. Responsibilities: Drive team execution, proactively resolve bottlenecks and make decisive trade-offs. Partner with cross-functional teams (Product, Design, Marketing, Science, and Analytics) to define the team's strategic direction. Translate high-level business goals into actionable projects. Own a team roadmap from conception to delivery, managing cross-team dependencies and mitigating risks. Maintain operational excellence through contributing to best practices for observability, reliability, and on-call processes. Ensure technical excellence through architecture reviews, tech debt management, and engineering guidance. Maintain team health by creating and refining team processes, fostering a supportive team culture, and managing resourcing. Develop team member careers by matching them with opportunities, setting clear expectations, and providing timely feedback. Build relationships across engineering teams to share learnings, align on standards, and identify collaboration opportunities. Serve as a dependable, high-bar interviewer and active participant in Lyft’s broader community. Experience: BS/MS or equivalent in Computer Engineering, Computer Science, or a related field, or equivalent practic

L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -73.4%
Quick readStrong listing-quality and freshness signals

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft's Customer Care Operations organization manages over 1.7 million monthly customer interactions and serves as the company's primary direct touchpoint with riders, drivers, and businesses — spanning frontline support across multiple customer segments, a global BPO workforce, and the central functions that enable them to operate at scale. The Senior Manager of Support Excellence owns the enablement infrastructure that determines whether Lyft's support operation can scale efficiently, react nimbly, and maintain high standards: Knowledge Management, Quality, Learning & Performance, and Tooling Enablement. This is not a role for someone who wants to maintain and optimize — it's a role for someone who wants to reimagine. The right person brings a bold, integrated vision for how these functions work together with Operations, Product, and Technology to improve customer outcomes and accelerate Lyft's evolution into an AI-native, human-enhanced support organization. They will set the direction, hold the bar, and move at the pace the environment demands — with the industry expertise to know what "great" looks like and the conviction to pursue it. Reporting to the Director of Business Planning & Central Operations, this role leads a team of 4-6 direct reports and 40-50 indirects, each owning a distinct function on the team team. Responsibilities: Vision & Strategy Define and own an ambitious, integrated vision for how Knowledge Management, Quality, Learning & Performance, and Tooling Enablement work together — not as separate functions, but as a unified enablement system that improves customer outcomes and advances Lyft's AI-native support evolution. Expand active AI fluency to every function in the portfolio — from how knowledge is structured for AI retrieval, to how quality signals feed mod

L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -73.4%

C$149.6K – C$187K/yr

Quick readStrong listing-quality and freshness signals

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities: Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions. System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems. Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically eva

PythonMachine LearningAIGo
L
📍 San Francisco, CA· Full-time
✓ High-confidence listingCompany trend -73.4%
Quick readStrong listing-quality and freshness signals

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities: Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions. System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems. Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically eva

PythonMachine LearningAIGo
L
📍 San Francisco, CA· Full-time
✓ High-confidence listingCompany trend -73.4%
Quick readStrong listing-quality and freshness signals

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Mapping team at Lyft is tasked with building a digital representation of the physical world - a map. We collect and serve the freshest and most accurate mapping data possible, along with algorithms, models, platform services, and map-based user experiences that power Lyft’s current and future transportation offerings. Mapping represents a huge opportunity for Lyft’s business, but also a big challenge. We build and scale systems that deal with large data storage, real-time data processing, machine / deep learning pipelines, routing and ETA models, driver and passenger location tracking, and more. We built beautiful and magical user experiences on top of all those services, and compete with companies that have been in the mapping business for decades. To strengthen our efforts, we are hiring a Senior ML Engineer who will work end-to-end on creating and improving new capabilities to detect changes in the environment and reflect them in our Lyft map using a wide variety of input sources from the Lyft fleet. For this we are looking for someone who values software engineering best practices, loves the algorithmic and geospatial side of the challenge and is data-driven from start to end. Our technology stack ranges from basic machine learning models to large language models and running them at scale on millions of images. You will work with incredibly passionate and talented colleagues from machine learning, data science, and engineering on projects that delight our passengers and drivers – powered by an up to date map. Responsibilities: Partner with Engineers, Data Scientists, Product Managers, and Business Partners to apply machine learning for business and user impact Perform data analysis and build proof-of-concept to explore and propose ML solutions to both new and existing proble

PythonGitMachine LearningAI
L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -73.4%

From C$118.8K/yr

Quick readStrong listing-quality and freshness signals

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Machine Learning is at the heart of Lyft’s products and decision-making. Machine Learning Engineers at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges, from pricing and marketplace frameworks that ensure reliability and competitiveness, to agentic AI platforms that automate analytical workflows, to behavioral detection systems that protect the integrity of our network. We operate at the intersection of applied ML and real business impact, shipping models that directly influence revenue, rider experience, and partner trust. Lyft Business builds products that help organizations move the people who matter most—employees, customers, patients, and guests—easily and efficiently. Our offerings include Business Travel, Lyft Pass, and Concierge (for healthcare and non-healthcare rides), enabling companies to manage transportation at scale through APIs, integrations (e.g., Concur, Expensify), and dedicated tools. These platforms power high-impact B2B use cases across corporate travel, healthcare access, customer experience, and community programs. We're looking for a Machine Learning Engineer to design, build, and deploy ML systems across Lyft Business. This is a high-scope role: you won't be siloed into one problem area. Instead, you'll move across pricing algorithms, fraud and behavior detection, agentic AI systems, and emerging ML applications as the business evolves. You'll write production-quality code, own models end-to-end from prototyping through deployment, and collaborate closely with Data Scientists, Product Managers, and Software Engineers to translate complex business problems into scalable ML solutions. This role is ideal for someone who is technically versatile, energized by variety, and wants to see th

AWSMachine LearningAIGo
L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -73.4%

From C$172K/yr

Quick readStrong listing-quality and freshness signals

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. As the Engineering Manager for the Lakehouse Foundation team, you will lead a group of engineers responsible for the foundational data layer that all of Lyft's data systems and emerging AI workloads are built on. The team owns catalog and metadata management, table formats and storage, and the access patterns and gateways through which other engineering teams interact with Lyft's data. As Lyft converges on a unified lakehouse architecture, this team builds and operates the single source of truth that powers analytics, machine learning, experimentation, and every business decision made from data. You will play a key role in shaping the team's technical direction, partnering with peer Data Platform teams on a multi-year platform evolution, and developing engineers who operate with autonomy on systems of significant scale and complexity. Lyft's Infrastructure teams build the foundational systems that the rest of engineering depends on to move fast, ship reliably, and scale efficiently. These are high-leverage roles where the work you and your team do has a multiplicative effect across the company. We're looking for experienced leaders who can balance the discipline of operating critical infrastructure with the curiosity to keep evolving how Lyft builds. Engineering at Lyft is a place where managers and engineers operate with high ownership and strong technical judgment. Our engineers expect their managers to be honest, available, and focused on the work that matters: developing their teams, removing obstacles, and giving people the support they need to do their best work. We build teams that are inclusive, technically rigorous, and have a strong sense of ownership for what they build. Responsibilities: Lead a team responsible for Lyft's foundational data layer, including catalog and metadata management,

RestMachine LearningAIGo
L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -73.4%

From C$108K/yr

Quick readStrong listing-quality and freshness signals

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. As a Data Scientist in the Pay, Integrity & Identity org, you will collaborate with our world class team of engineers, product managers, analysts and other data scientists to help create best in class pay platforms, stop fraudulent actors from harming our riders & drivers fraud and build user trust on the Lyft platform. You will run experiments (A/B tests) and develop data driven solutions to launch new features and remove the bad actors from the Lyft platform while maintaining a positive experience for genuine users. We’re looking for an intellectually curious individual who has extraordinary attention to detail, a track record of analytical problem-solving and skilled communication. Prior experience in the fintech, fraud or identity space is preferred. Responsibilities: Design and analyze experiments in collaboration with other scientists, product & engineering; communicate findings to stakeholders and facilitate launch decisions Leverage advanced statistical techniques to generate quantitative insights and develop machine learning models Analyze the wide variety of signals available to identify patterns in large datasets and uncover root causes Partner with product managers, engineers, and operators to translate analytical insights into decisions and action Build data pipelines and develop analytical frameworks to monitor business and product performance Set business metrics that measure the health of our products, as well as passenger and driver experience Collaborate with product and engineering and communicate findings to stakeholders in a clear and concise manner Experience: Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience 4-6+ years of industry experi

PythonSQLMachine LearningAI
L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -73.4%

From C$1.3M/yr

Quick readStrong listing-quality and freshness signals

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Safety and Customer Care (SCC) team at Lyft manages over 1.7 million monthly human and AI interactions and serves as Lyft's primary direct touchpoint with riders and drivers. We handle critical infrastructure that powers both human associates and AI agents to make riders and drivers feel safe and comfortable while riding or driving with Lyft, transforming every support interaction into a moment of genuine connection. As a Data Scientist working on Causal Inference in SCC, you'll partner with a strong team of engineers, product managers, designers, and operations leaders to deliver a personalized and exceptional experience for Lyft customers, using rigorous causal inference to guide the highest-stakes decisions we make. We're looking for a motivated and talented Data Scientist with deep causal inference expertise to join the SCC Data Science team. You'll partner closely with the area's tech lead on high-impact work spanning AI-powered support products, differentiated service, and operations optimization. The ideal candidate brings sharp applied inference intuition, a bias toward impact, and the ability to cut through ambiguity in complex problem spaces. You'll work on projects like: Design rigorous experiments and quasi-experiments to measure the causal impact of SCC product and AI-agent launches, and drive data-informed launch decisions. Build causal ML models to optimize concession budget allocation, targeting the right support credit, to the right rider or driver, at the right moment to maximize trust and business impact. Quantify the long-term effects of support-experience changes on rider and driver retention, and uncover heterogeneous treatment effects across our community. Deliver strategic insights on quality–cost tradeoffs, empowering leadership to balance service quality, coverage,

PythonSQLAIGo
L
📍 San Francisco, CA· Full-time
✓ High-confidence listingCompany trend -73.4%
Quick readStrong listing-quality and freshness signals

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. As an Applied Scientist specializing in Machine Learning and Operations Research on this team, you will develop mathematical models and launch algorithms that power these key pricing and ETA decisions. You will leverage your skills to build ML and optimization models and productionalize pipelines that can scale to millions of calls per day while solving critical business problems that have a big impact on the marketplace and rider experience. You will get exposure to a diverse set of real-world problems across optimization, prediction, machine learning, and inference and collaborate closely with teammates and stakeholders across Pricing, from Product Managers to Engineers and Analysts. We are looking for someone who is excited about working in a fast-paced, innovative, and impactful environment, and is adept at balancing complexity and efficiency to translate real world business problems into reliable solutions, systems and decision frameworks. Responsibilities Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context Write production quality code. Design, build and deploy production-grade ML and Optimization models. Able to build custom methods and tooling beyond off-the-shelf libraries. Perform data analysis and build proof-of-concepts to explore and propose ML and Optimization solutions to both new and existing problems. Evaluate machine learning systems against business goals. Collaborate with Engineers to implement algorithms in live systems and ensure the robustness of the systems Establish metrics and development measurement methodologies to monitor the health of our products, as well as the impacts on user and marketplace outcomes Drive collaboration and coordination with cross-functional teams

PythonMachine LearningAIGo
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