Jobs in Canada

Go To Market Programs Manager in Toronto

292 active opportunities · Updated October 2026

Explore current go to market programs manager jobs in Toronto. Filter by work mode, employment type, experience, department, date posted and distance.

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

From C$1.4M/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. Agentic AI is at the center of how we scale that mission. We fine-tune and align open-source models, build AI-powered support agents, and develop end-to-end AI agents for safety case management, systems that reason over complex, high-stakes cases and drive them to resolution. SCC brings together ML, data, backend, and product engineers alongside data scientists and operations partners to transform these systems. As a Machine Learning Engineer on the SCC team, you will fine-tune and align models and build AI Agents that power how riders and drivers get help. Your work spans the full loop: post-training open-source models for our domain, composing them into multi-step agents, and building the evaluation that proves they are safe to ship in a customer-facing, safety-critical setting. Post-train and adapt open-source LLMs for SCC use cases using SFT, LoRA, and preference-tuning methods (RLHF, RLAIF, RLVR). Design and build AI-powered support agents and end-to-end agents for safety case management using LangGraph or equivalent agentic frameworks. Own the evaluation data flywheel, offline and online, that defines what "good" looks like and build benchmarks for the team to hill-climb. Turn interaction feedback into training data and learning signals, closing the data flywheel that continuously improves the models. Responsibilities: Conduct literature review and build post-training fra

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

From C$96K/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. Trust and confidence is fundamental to the Lyft marketplace, and the Pay, Integrity & Identity (PII) Analytics team is charged with providing and ensuring that trust and safety to all customers. The PII Analytics team is one of the most critical teams that helps protect Lyft and enables the company to grow in a sustainable way. The team is fast-paced, high-energy, and meticulous in diagnosing emerging fraud patterns and preventing fraud loss before it can happen. We drill holes in all the products we launch and obsess over how to make our business impervious to fraud vectors. The team conducts a rigorous analysis of complex data sets and sets up multiple layers of business rules, models, and other processes to prevent potential fraud. We are a highly cross-functional team and regularly engage in discussion and reviews with stakeholders to prioritize plans for reducing fraud impact and introducing safety features. We’re looking for a rock-star to join a fast-paced environment to contribute to Fraud-related analysis and operations. This individual is responsible for investigating and developing solutions to prevent and mitigate third party fraud. This person will proactively identify fraud patterns and sources to minimize the company’s exposure to financial and reputational risk. The Senior Analyst will take ownership over multiple discrete fraud segments to develop and execute a strategy which addresses fraud in the earliest stages of detection. The Senior Analyst will define fraud prevention measures that are mindful of the impact on good user experience while inhibiting fraud actors’ ability to reach our platform. This person is quantitatively driven, detail-focused, and operations-savvy while ensuring the best possible customer experience. This individual possesses a high level of subject matte

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

From C$136K/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. Lyft is looking for software engineers from a scope of disciplines. We are growing our team with people who want to build, improve and incorporate technologies that make the lives of our community more enriched. As an engineer at Lyft, you'll collaborate with teams like product, data science, analytics, and operations on code that empower us to iterate quickly, while focusing on delighting our passengers and drivers. The Applied AI team is looking for a Backend Engineer to join the AI Entries team. You will build the foundational infrastructure that connects Lyft to emerging AI ecosystems and devices and architect the APIs and orchestration layers that allow third-party agents and multimodal interfaces to interact with Lyft. By building these robust integration, you will help make Lyft available where our riders are. Responsibilities: Establish engineering best practices and patterns; help uplift the team's craft and drive a culture of engineering excellence Drive high-impact projects and innovate new solutions to deliver the best user experience Produce and drive scalable system design for large, complex features — from idea through execution and launch Mentor engineers on the team, providing technical guidance and supporting their growth Write well-crafted, well-tested, readable, maintainable code Participate in code reviews to ensure code quality and share knowledge across the team Participate in the team's on-call rotation; identify, triage, debug, and resolve issues across our applications and platforms Have the ability to explain the various trade offs made in decisions Manage project priorities, deadlines, and deliverables. Experience: BS/MS or equivalent in Computer Engineering, Computer Science, or related field or equivalent practical experience. 5+ years of software engineering/production

PythonSQLPostgreSQLAWS
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
📍 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$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
📍 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. Marketplace teams are at the heart of our products and decision-making, owning everything from rider pricing to driver earnings, incentives, and efficient matching. We’re looking for passionate, driven engineers to build systems that empower our riders and drivers to have the best transportation experience possible through prediction, adaptivity, and personalization. We’re looking for someone who is excited about working in a fast-paced, innovative, and impactful environment to create reliable solutions to distributed computing, ML, and data problems. The Pricing team is a centerpiece of Lyft’s Marketplace org, determining prices for all rideshare products and supporting new initiatives. Rider Engagement develops rider-facing engagement levers and optimizes user pricing experience to drive both short term and long term business outcomes. We work with Product & Science to solve and implement complex pricing requirements, balancing the needs of riders, drivers, and the business goals. As an owner of one of the most critical flows in the company, you will work on a wide array of challenges such as latency-sensitive concurrency problems, large scale distributed systems, and experimentation. If you’re interested in playing a large part in demand / supply management and improving the Lyft customer experience, this could be a great fit for you. Responsibilities: Drive high-impact projects and innovate new solutions to provide the best user experience. Work closely with cross-functional teams and partner teams to develop solutions based on technology and business needs, and advance team’s goals and priorities Independently lead features from idea to positive execution and launch Unblock, support and communicate with internal partners to achieve results Write well-crafted, well-tested, readable, maintaina

PythonAWSRestAI
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 Frontend Software Engineer on the Operator Core Tooling pod, you'll play a vital role in building the robust services that power our critical operations tooling platform. Your work will directly empower our micromobility operations teams by providing them with intuitive and efficient tools, significantly improving their daily workflows as they manage our fleet. You'll collaborate closely with business leaders, front-end developers, and data scientists across Lyft to achieve this impact. Responsibilities: Help define the roadmap and architecture based on technology and business needs Write well-crafted, well-tested, readable, maintainable code Have a good grasp and ability to explain the various tradeoffs made in decisions Participate in code reviews to ensure code quality and distribute knowledge Lead projects from idea to positive execution Incorporate considerations for business context and failure modes in your work Proactively participate in resolving ongoing incidents Unblock, support, effectively communicate and obtain buy-in across teams to achieve results Share your knowledge by giving brown bags, tech talks, and evangelizing appropriate tech and engineering best practices See the direct impact of your work on the efficiency of our operating teams Experience: 3+ years of software engineering industry Advanced knowledge of JavaScript Experience working with modern JavaScript frameworks, like React Experience working with NodeJS and Express applications Experience working with design systems (e.g. Bootstrap, Salesforce Lightning, GitHub Primer) Good understanding of web performance and how browsers and DOM work Experience with unit, integration, and end-to-end testing Experience designing, building and improving a set of team owned components Culture of investigating and solvin

JavaScriptJavaReactNode.js
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. We are building and maintaining a highly scalable asynchronous platform that empowers our organization to handle critical business cases. As a software engineering team, our mission is to create robust and innovative solutions that drive the success of our business and deliver unparalleled value to our customers. We adopt Infrastructure as Code practice to automate the provisioning and configuration of our resources, which helps reduce manual configuration and improve consistency. Our team culture is built on collaboration, open communication, and a supportive environment where each member's ideas are valued and contributions are recognized. We believe in the importance of fostering a positive workplace culture that inspires innovation and creativity. Responsibilities: Maintain and analyze metrics from; operating systems; control planes; and applications to assist in fault detection and performance enhancement Design, develop and deploy tooling and systems that continually improve the reliability, scalability and efficiency of our platform Balance feature development speed and reliability with service-level objectives Operate and improve our Infrastructure using industry best practices and tools Participate in design and production readiness reviews, platform management and capacity planning ceremonies with cross-functional teams Document Infrastructure operations process and insights, identify repeatable actions and ruthlessly automate repetitive tasks Participate in our teams on-call rotations, respond to incidents and support other teams mitigate customer impacting events Experience: 5+ years experience working on teams responsible for software development, automation and systems engineering Experience building large-scale infrastructure, distributed systems or networks. Knowledge with SQS,

PythonAWSAzureGCP
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. Our Infrastructure team is passionate about building software to solve problems at massive scale. We do this often, and when we believe our solution is worth sharing with the community, such as Envoy Proxy , we open source our ideas for the benefit of others. As an Observability team member, you are responsible for the operation and maintenance of our logging and metrics infrastructure. You ensure all teams at Lyft are aware of the operational health of their products by monitoring system availability and take a holistic view of our platform performance. You build software and platforms to automate infrastructure platform operations and management. By measuring and monitoring our operations you find opportunities to improve our systems in order to push our platform forward. You provide our partners with the support they need to help them build robust large scale distributed systems. We count on the reliability of our infrastructure to empower Lyft teams to provide our customers rich experiences that are highly available with rock solid performance to ensure our transportation platform continues to connect people and places. As we grow our team, we are seeking experienced Infrastructure Engineer to ensure that as our Infrastructure continues to scale, our platform continues to provide an essential and dependable service that transports millions of people every day. Specifically we are searching for someone who brings fresh perspectives, enjoys collaborating with cross-functional teams in order to continually improve our products and services for our customers. Responsibilities: Maintain, improve, and develop tooling and systems that enhance the reliability, scalability, and efficiency of our platform. Assist engineering teams in defining service-level objectives (SLOs) and provide the necessary toolin

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

From C$136K/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. Our core philosophy is to empower developers to self-serve rather than be bottlenecked by a central quality team. We believe that by creating smart, automated tooling, we can eliminate common roadblocks, making developers happier and more productive. The Rider Quality team is focused on elevating quality, testing, and accessibility across our mobile platforms. We are currently shifting our strategy to heavily leverage automation and AI to revolutionize how we approach testing. We're not doing traditional QA - we're building the future of quality engineering. This is a chance to step into a Senior role where you won't just write code; you'll design systems that define how hundreds of engineers deliver product faster, happier, and with fewer bugs. We are fundamentally shifting away from manual processes and existing automation frameworks that struggle to keep up, betting heavily on Artificial Intelligence and agentic frameworks to drive a massive "shift left" in our organization. Success in this role is measured by tangible impact, including increased developer satisfaction, engineering hours saved, and bugs/incidents avoided in production. We are seeking a highly skilled and innovative Senior Software Engineer to join our team. You will be instrumental in building the next generation of our quality assurance platform. You will be responsible for designing and developing advanced AI-powered tooling for test case generation, review, and execution. Your work will directly impact our ability to provide fast, actionable feedback to developers, "shifting left" to ensure quality from the earliest stages of development. You will play a key role in integrating these tools into our existing developer workflows, ensuring seamless adoption and maximum impact. We are looking for someone with a strong background in

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

$136K – $170K/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. Marketplace teams are at the heart of our products and decision-making, owning everything from rider pricing to driver earnings, incentives, and efficient matching. We’re looking for passionate, driven engineers to build systems that empower our riders and drivers to have the best transportation experience possible through prediction, adaptivity, and personalization. We’re looking for someone who is excited about working in a fast-paced, innovative, and impactful environment to create reliable solutions to distributed computing, ML, and data problems. The Pricing team is a centerpiece of Lyft’s Marketplace org, determining prices for all rideshare products and supporting new initiatives. We work with Product & Science to solve and implement complex pricing requirements, balancing the needs of riders, drivers, and the business goals. As an owner of one of the most critical flows in the company, you will work on a wide array of challenges such as latency-sensitive concurrency problems, large scale distributed systems, and experimentation. If you’re interested in playing a large part in demand / supply management and improving the Lyft customer experience, this could be a great fit for you. Responsibilities: Help define the roadmap and architecture based on technology and business needs Unblock, support, effectively communicate, and obtain buy-in across teams to achieve results Lead projects of multiple people from idea to positive execution Write clear, scalable and clear design documentation Write well-crafted, well-tested, readable, maintainable code Utilize your expertise in Python, Golang, AWS to deliver robust and scalable solutions Participate in code reviews to ensure code quality and distribute knowledge Proactively participate in resolving ongoing incidents Share your kno

PythonAWSAzureGCP
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. Our mission depends on having a digital representation of the physical world - a map with all routing related (real-time) information. This is what makes Lyft different from many products: our products don’t just facilitate online interactions, they facilitate dynamic, real-world ones. Without mapping services, none of these real world interactions between people and transport can happen. The Mapping organization at Lyft has spent the last few years building up Lyft’s mapping assets and capabilities by combining many internal and external data sources and services into an increasingly powerful and mission-critical technology stack. In doing so, we’ve also enabled new user experiences and features across all of Lyft’s products, including rideshare industry leading firsts like CarPlay, Android Auto, and real-time driver feedback! We are hiring a Software Engineer to join our Mapping experiences team that builds end user features to enhance drivers and riders experience on Lyft’s platform by using our in house navigation system. We are looking for an engineer with expertise in system architecture, cross team collaboration, and experience in building scalable solutions in the cloud environments. In this role, you'll collaborate with engineering, product, data science, analytics, operations, and AI/ML teams on programs that empower us to iterate quickly, delighting our passengers and drivers with rideshare focused mapping experiences. Responsibilities: Drive high-impact projects and innovate new solutions to provide the best user experience Lead large features from idea to positive execution and launch Write well-crafted, well-tested, readable, maintainable code Participate in code reviews to ensure code quality and distribute knowledge, as well as on call rotations Share your knowledge by giving brown ba

PythonSQLAWSAzure
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 Engineer on the SCC team, you will have ownership over the data modeling and pipelines that power SCC’s Associate and AI Agent Platform . Your efforts will be critical to the reliability of our pipelines, execution of third party data integrations, accurate reporting of agents performance, and efficiency improvements that can save millions of dollars / year. You will work cross-functionally to bridge Lyft's business goals with data engineering. Your efforts will allow access to business and user behavior insights, using huge amounts of Lyft data to fuel several teams such as Analytics, Data Science, Engineering, and many others. Responsibilities: Owner of the core data pipeline, responsible for scaling up data processing flow to meet the rapid data growth at Lyft Evolve data model and data schema based on business and engineering needs Implement systems tracking data quality and consistency Develop tools supporting self-service data pipeline management (ETL) SQL and MapReduce job tuning to improve data processing performance Write well-crafted, well-tested, readable, maintainable code Participate in code reviews to ensure code quality and distribute knowledge Collaborate cross-functionally with product, engineering, data science, and marketing teams to understand business problems and align on prioritization and solutions Experience: Bachelor's degree in Compute

PythonSQLAWSRest
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