Content Management Sr Analyst Jobs

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 over half a billion rides and counting, Lyft is solving hard problems in a flourishing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Growth and beyond. We're actively building the next-generation Machine Learning (ML) platform for low-cost, ultra-immersive transportation to improve people’s lives using modern ML with peta-byte scale data. Our Machine Learning Engineers are excited to work on these challenging problems and redefine solutions to directly impact various aspects of Lyft's primary business. If you are a student with experience in machine learning workflows, passionate about solving challenging problems using data and working in a dynamic, creative, and collaborative environment, this opportunity is for you! Responsibilities: Contribute to the design, build, train and test of Machine Learning models Write production-level code to convert ML models into working pipelines Partner with Product Managers, Data Scientists, and fellow ML Engineers to frame Machine Learning problems within the business context Analyze experimental and observational data, communicate findings to support decisions Participate in code and spec reviews to ensure code quality and distribute knowledge Experience: Currently pursuing a Bachelor's, Master's, or PhD degree in Computer Science or a related technical field from a university in Canada (required) , with a graduation date between December 2027 and Summer 2028 (required). For any candidates who are master's students who worked between their bachelor's and master's programs: candidates should also have less than 2 years of relevant full-time work experience Available during Summer 2027 for the internship in Toronto Good understanding and knowledge of ML libraries like scikit-learn, Tensorflow, PyTorch, Keras, MXNet, et

About the Team OpenAI is building the next generation of advertising for an AI-powered world. As AI changes how people discover information, explore possibilities, and make decisions, we believe this presents a huge opportunity for small and medium-sized businesses to connect with customers in new ways. The SMB Ads Marketing team is building this opportunity from the ground up. We define how businesses discover OpenAI’s advertising platform, become successful advertisers, and grow their investment over time. Working closely with Product, Ads Engineering, Data Science, and Sales, we combine customer insight, rigorous experimentation, and fast execution to turn early opportunities into scalable growth. About the Role We are hiring a Lead, Ads Prospecting & Growth Intelligence to build the intelligence and orchestration platform powering OpenAI’s ads business. This person will help us identify the right companies and people, understand why they are relevant, determine the right next action, and learn from what happens afterward. Own the prospecting function for the ads business, serving SMB Ads while building a foundation reusable across segments. Set the vision, operating model, roadmap, platform choices, business rules, adoption, and outcomes; and partner with Ads Engineering, Data Science, and internal platform teams. Decide what to build in-house, enable through internal platforms, or deliver through selected vendors and partners. In This Role, You Will Lead the function’s strategy, roadmap, operating model, and adoption. Connect platform investments to measurable advertiser and business outcomes. Define a unified prospect, account, contact, and advertiser data model. Establish standards for identity, data quality, provenance, freshness, confidence, and consent. Combine market, intent, behavioral, product, CRM, campaign, and customer-success signals to improve targeting and customer engagement. Design enrichment and verification workflows. Evaluate in-house cap

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 over half a billion rides and counting, Lyft is solving hard problems in a flourishing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Growth and beyond. We're actively building the next-generation Machine Learning (ML) platform for low-cost, ultra-immersive transportation to improve people’s lives using modern ML with peta-byte scale data. Our Machine Learning Engineers are excited to work on these challenging problems and redefine solutions to directly impact various aspects of Lyft's primary business. If you are a student with experience in machine learning workflows, passionate about solving challenging problems using data and working in a dynamic, creative, and collaborative environment, this opportunity is for you! Responsibilities: Contribute to the design, build, train and test of Machine Learning models Write production-level code to convert ML models into working pipelines Partner with Product Managers, Data Scientists, and fellow ML Engineers to frame Machine Learning problems within the business context Analyze experimental and observational data, communicate findings to support decisions Participate in code and spec reviews to ensure code quality and distribute knowledge Experience: Currently pursuing a Bachelor's, Master's, or PhD degree in Computer Science or a related technical field from a university in Canada (required) , with a graduation date between December 2027 and Summer 2028 (required). For any candidates who are master's students who worked between their bachelor's and master's programs: candidates should also have less than 2 years of relevant full-time work experience Available during Summer 2027 for the internship in Toronto Good understanding and knowledge of ML libraries like scikit-learn, Tensorflow, PyTorch, Keras, MXNet, et

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 Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem Write production modeling code; collaborate with software engineers to implement algorithms in production Design and run both simulated and live traffic experiments Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree at a university in Canada (required) in mathematical sciences ( Opera

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 Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem Write production modeling code; collaborate with software engineers to implement algorithms in production Design and run both simulated and live traffic experiments Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree at a university in Canada (required) in mathematical sciences ( Opera

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 Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem Write production modeling code; collaborate with software engineers to implement algorithms in production Design and run both simulated and live traffic experiments Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree in mathematical sciences ( Operations Research, Computer Science, Statistic

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 Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem Write production modeling code; collaborate with software engineers to implement algorithms in production Design and run both simulated and live traffic experiments Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree in mathematical sciences ( Operations Research, Computer Science, Statistic

About DevRev At DevRev, we're building the future of work with Computer – your AI teammate. Unlike traditional tools, Computer unifies all your data sources, tools, and workflows into a single AI-ready platform, giving employees real-time insights, proactive suggestions, and powerful agentic actions. It extends your existing software with AI-native apps and agents that work alongside your teams and customers – updating workflows, coordinating across teams, and eliminating repetitive work. We call this Team Intelligence: human-AI collaboration that breaks down silos, brings people back together, and frees you to solve bigger problems. Backed by Khosla Ventures and Mayfield with $150M+ raised, DevRev is trusted by global companies across industries. About the role DevRev is hiring a Senior Product Manager for the Computer Data and Analytics Platform – a hands-on product leader who will own the trusted data foundation that makes Computer precise, useful, and safe across every experience. Computer should not merely report on work. It should understand customer, product, and operational context; reason across it; and help people and agents take the right action. The Computer Data and Analytics Platform makes that possible through a unified, governed, low-latency data layer that turns data from DevRev and connected systems into durable context for humans, applications, analytics experiences, and AI agents. You will define how data is captured, modeled, governed, queried, and activated across DevRev. The platform will support operational reporting and embedded analytics, while also enabling grounded, context-rich agentic conversations in Computer – helping users ask questions, investigate work, receive trusted answers, and take safe actions in the flow of work. This is a unique opportunity to build the foundation for an AI-native operating system – where customer context, product telemetry, structured records, events, and machine reasoning converge. What y

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are looking for an experienced Seoul-based Public Policy expert to lead Anthropic’s policy engagement in South Korea. In this role, you will advance practical AI governance and support Anthropic’s commercial expansion by building strategic relationships with Korean government authorities, developing substantive policy positions and papers, and engaging in regular outreach to drive progress in AI policy and AI safety. You will draw upon established relationships with key policymakers and their staff to shape how Korea approaches AI regulation and safety during a critical period of governance development. As part of this role, you will collaborate with a dynamic, geographically distributed policy team on a variety of projects, including analyzing policy proposals, drafting submissions to requests for public comment, planning and executing policy campaigns in Korea, and providing policy advice to technical colleagues. This is a foundational hire — you will be building Anthropic’s policy presence in Seoul from the ground up. Key responsibilities Conduct comprehensive mapping of key Korean AI policy stakeholders and build strategic relationships with government officials, think tank researchers, and civil society leaders across the national and, where appropriate, sub-national governmental levels Brief a diverse set of policy and research actors looking to better understand AI safety and AI policy opportunities in the Korean context Convene diverse stakeholders and speak at policy events such as research announcements, discussion panels, or workshops on AI safety topics Analyze emerging legislation and develop Anthropic’s

About the Team API Frontiers turns OpenAI’s frontier models into production APIs that developers can use to build reliable products and agents. We own the core path connecting models to developers through the Responses API, with a focus on safety, reliability, and speed. Working closely with Research, Safety, Codex, and other API teams, we bring new model capabilities into production and improve them through developer feedback. About the Role We are looking for a backend software engineer to build and operate the services behind the Responses API. You will shape API behavior, bring new capabilities from research into production, and make long-running agent workflows dependable and fast. The work combines distributed systems engineering with product judgment: designing useful developer interfaces, managing staged rollouts, and following production issues through to durable fixes. In this role, you will: Design, build, and operate APIs and backend services that bring frontier model capabilities to developers. Partner with Research, Safety, Codex, and API teams to define API behavior and deliver safe, staged launches. Build API capabilities for agent workflows, including task delegation, context sharing, and parallel execution. Strengthen long-running request reliability across timeouts, cancellation, streaming, and background execution. Improve request-processing performance and tail latency through profiling, efficient systems code, and persistent connections. Turn developer feedback and production failures into better observability, diagnostics, and lasting product improvements. Your background might look something like: 5+ years of experience building and operating backend services or developer-facing APIs in production. Strong software engineering fundamentals, with practical knowledge of distributed systems, concurrency, and asynchronous execution. Ability to diagnose production failures and performance bottlenecks using observability data and profiling. Product

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team Data Science at Stripe is a vibrant community where data analysts and data scientists learn and grow together. You'll work with some of the most fundamental data at Stripe, and use that data to help drive company-wide initiatives. We have a variety of Data Analytics roles and teams across Stripe and Data Analysts are hired in line with the business needs and domain of the organization they will support. What you’ll do We’re looking for a Data Analyst to partner with Stripe’s Global organization, helping millions of users sell around the world. You’ll help build analytics and data products for solutions such as Adaptive Pricing and Stripe Managed Payments, as well as Stripe’s expansion into new markets across LATAM and EMEA. Responsibilities Design and build scalable data models and infrastructure to power product analytics and metrics reporting as we launch and grow new products Own business-critical data products, including Tier-1 datasets and production pipelines, ensuring reliability through rigorous testing, monitoring, and documentation Build and maintain the metric definitions, metadata, and business context that enable AI agents to help stakeholders explore trusted data and answer business questions independently Develop dashboards, automated reporting, and thoughtful analyses to surface actionable insights and proactively identify business opportunities Partner closely with senior business leaders to translate business needs into ana

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are looking for a Solution Engineer who is accustomed to solving customers’ most complex problems, closing large deals, and positioning organizations to enable Analytics and AI adoption quickly and easily. In this role, you will work directly with the sales team and channel partners to understand the needs of our customers, strategize on how to navigate winning sales cycles, provide compelling value-based demonstrations, product fit conversations, and support enterprise Proof of Concepts. As a Snowflake Solution Engineer, you must share our passion for reinventing the data landscape. You should have a proven track record of helping customers modernize their data stack to unlock Analytics/AI/ML capabilities. You are equally comfortable in both a business and technical context, interacting with executives about Data, Analytics & AI strategies and "talking shop" with technical audiences about implementation. Location: Must be located in or near Bogota, Colombia IN THIS ROLE YOU WILL GET TO: Present Snowflake technology and vision to executives and technical contributors, specifically focusing on how Snowflake serves as the engine for rapid AI innovation. Work hands-on with prospects to demonstrate the value of Snowflake throughout the sales cycle, moving them from initi

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Responsibilities and Tasks Product Quality (PQ) Predictive Solutions: Build and productionize machine learning models (classification and regression) to support predictive and prescriptive analytics across semiconductor test and manufacturing processes. Agentic AI and LLM Development: Contribute to the design and implementation of multi-agent systems for PQ workflows, including code generation, automated troubleshooting, and process optimization. Work with retrieval-augmented generation (RAG) pipelines: identify data sources, develop retrieval strategies, and improve context quality for LLM-based applications. Assist in implementing tool-using capabilities, function calling, and agent memory systems. Software Engineering and Productionalization: Develop maintainable code and analytical pipelines suitable for high-volume manufacturing environments. Optimize for performance, latency, and token efficiency. Collaborate with senior team members on testing, deployment, and monitoring. Communicate analytical insights, model behavior, and results clearly to technical and non-technical stakeholders Integ

Why Harvey At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. Role Overview Spaces bring people, context, and agents together in one place. They help legal teams organize their work, collaborate securely, and use Harvey across the lifecycle of a matter or project. We’re looking for a Senior or Staff Product Manager to own the core Spaces experience. You will shape how users create and navigate Spaces, bring in relevant context, run work, and return to Spaces as an ongoing part of their workflow. You’ll also lead the work required to make the product intuitive, polished, and broadly adopted across Harvey’s customers. This is a senior individual-contributor role for someone with excellent product judgment, strong design instincts, and the ability to turn an ambitious, ambiguous problem into a clear strategy and shipped product. What You'll Do Ow

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . As a Senior Software Engineer on the Blockchain Networks team within the Platform group, you'll build the critical infrastructure that integrates blockchain protocols with Coinbase's internal services for new assets, stablecoins, and staking. This team translates complex blockchain operations and state machines into simple, reliable APIs that product teams across Coinbase depend on. You'll own multi-quarter technical initiatives and ship platform primitives that directly improve the latency, reliability, and cost of our crypto stack. What you'll do: Own the design and delivery of blockchain network infrastructure that abstracts blockchain complexity into reliable, platform APIs Lead multi-quarter initiatives including new chain integrations, re-architecture efforts, and data migrations that improve system latency, reliability, and cost Define and maintain APIs, SLOs, and observability for the systems you build, including on-call ownership Partner with product and platform teams to establish data contracts and ship SDKs and platform primitives that drive adoption across Coinbase Build deep technical context across multiple top blockchain protocols (e.g., Bitcoin, Ethereum) and apply that knowledge to simplify cross-chain operations Required Skills and Experience: 5+ years of software engineering experience, with demonstrated ownership of production services in a servi