Gtm Compliance Analyst in San Francisco

Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. About The Role & Team Amplitude’s Revenue Accounting team is looking for a Sr Billing & Collections Analyst to own critical components of our order-to-cash process, ensuring customers are billed accurately, invoices are delivered on time, and billing issues are resolved quickly. In this role, you’ll manage the end-to-end billing cycle across our revenue streams while partnering closely with customers and internal teams across GTM and Finance. You’ll also play an important role in improving our billing and collections processes, with an opportunity to help move our order-to-cash workflows toward greater automation and scale. This is a hands-on role for someone who is highly detail-oriented, comfortable managing volume and deadlines, and enjoys solving complex problems in a cross-functional environment. As a Sr Billing & Collections Analyst

About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About the Team Marketing at Snorkel is growing rapidly and anchored by high-ownership operators who lead independently, align cross-functionally, and consistently deliver outsized results. We partner across Sales, Product, Research, and the executive team to translate complex AI and data value into differentiated positioning, integrated programs, and field-ready enablement that accelerates growth. The culture is high standards, high autonomy, and high collaboration. About the Role Reporting to the Sr. Director of Product Marketing, the Product Marketing Manager, Frontier Labs will own the GTM execution for our frontier lab business. You will partner closely with Research, FDE, and frontier-facing sales teams to translate technical work into research-credible positioning, repeatable sales plays, and high-quality GTM programs that resonate with research and procurement leaders inside frontier labs. You will keep the frontier asset library (battlecards, technical one-pagers, decks, benchmark and eval narratives) sharp against a fast-moving market, and bring competitive and customer insight into every motion. This is a hands-on role for a product marketer who wants

About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! The Role We're looking for our founding AI Data Product Manager to own Snorkel's Agentic Data and RL Environments roadmap. In this role, you'll lead the product strategy for a variety of data types (e.g. Agentic Coding, Computer Use). You will shape the roadmap for the datasets Snorkel invests in by understanding the market, incorporating frontier lab needs and collaborating with researchers at Snorkel and our academic partners. This role is highly cross-functional, sitting between Research, GTM and Operations. As a founding member for this role, you will be in charge of setting up the frameworks to build the roadmap, gather data from relevant sources, and share the roadmap with both internal and external stakeholders. What You'll Do Own the "data as a product" roadmap for Snorkel's Agentic and RL Environment focus areas, working x-functionally with research, academic partners, and GTM to define the skills and capabilities for our datasets Shape new "data" product areas and work with academic partners and research leaders to build Snorkel's competitive edge in the market Collaborate cross-functionally to help shape the roadmap and data strategy and influence bu

Data Engineer, Data Platform About the Role We are building out our Data Platform team at Sigma, with a relentless focus on developing data models that fuel trusted insights across the company. As a Data Platform Engineer, you will be responsible for the underlying data architecture across Snowflake and Databricks, as well as building and optimizing various ETL pipelines to fuel both internal and external (demo) use cases. Reporting to the VP of Data & Revenue Engineering, this is a high visibility role with the opportunity to work on greenfield projects. If you’re a data engineer with a builder mindset who wants to leverage a best-in-class stack, and genuinely is invested in Sigma’s mission, let’s chat! What You Will Be Doing Architect and manage our production data pipelines in Snowflake and how they are consumed in Sigma ( Tech we use : Fivetran, dagster, dlt, terraform, dbt, Snowflake, Sigma, Hightouch, Metaplane) Build foundational processes for scaling our demo asset data across various Cloud Data Warehouses Scale our terraform deployment across all of our Snowflake assets Continue to advance our data governance policies Work cross functionally to accomplish all of the above! You’ll work across Product, Engineering, GTM—with users of all skills and levels Qualifications We Need Strong knowledge and experience of working with APIs and building data pipelines from various systems into Cloud Data Platforms (e.g., Snowflake, Databricks) Strong communication and collaboration skills. You will primarily partner with the Analytics and Infrastructure Engineering teams internally at Sigma; your ability to work and collaborate closely with them will be integral to your success. Experience deploying data governance frameworks with a scalable and repeatable process Ability to thrive in ambiguous environments and get stuff done. We move fast and iterate quickly, and we want you to feel empowered to do exactly that 3+ years of relevant experience wor

Join the team shaping the future of AI at Scale. Scale builds RL environments: sandboxed replicas of the digital spheres where real knowledge work occurs and built from the operating data of the companies that actually hold it. As the Data Acquisition Lead , you will own the commercial motion that gets us that data end to end. You will figure out which companies sit on the data for the next domain worth owning and then go and get it. This is a zero-to-one function with no playbook. You should be prepared to wear many hats, from thesis-driven dealmaker to hands-on operator to technical translator between commercial and Research teams. You will: Map the supply side. Work backwards from where labs are pushing to the specific organizations holding the underlying data. Build a thesis on which domains are worth owning and in what order. Invent the deal structures. You'll work with Scale’s legal team to define the first version of how these transactions get priced. Close. Own it from cold outreach to signature. Close the loop with the technical side. You need to hold a real conversation about what makes a dataset trainable and become an expert in what makes this underlying data valuable. Build the machine. Do the work by hand first, then turn what you learn into a repeatable pipeline. Ideally, you’d have: 5+ years across some mix of business development, corp dev, commercial strategy, or early-stage GTM. The label matters less than a track record of building a commercial motion that didn't exist before you got there A strong track record of managing important external relationships Strong business judgment and the ability to evaluate partnership value quickly Clear communication skills and comfort working with senior stakeholders Ability to operate independently while staying closely connected to cross-functional teams A practical, hands-on approach to building new functions from the ground up Comfort working in fast-moving, ambiguous environments Experience in

Owns day-to-day deal pricing execution for Enterprise, including pricing calculations, staffing inputs, and dashboard reporting that gives Sales and Deal Desk leadership visibility into deal status, pricing, and margin. Partners with the Deal Desk Manager on customer deal structuring and on identifying ways to accelerate the deal approval process. What You’ll Do Deal Pricing Execution Manages day-to-day deal pricing calculations for Enterprise deals, including ROI modeling and EPD staffing inputs Applies existing pricing frameworks consistently across Land, Expansion, and Framework deals Partners with the Deal Desk Manager to design customer-specific deal structures for non-standard or complex deals Pricing & Deal Status Reporting Builds and maintains a pricing dashboard tracking deal status, pricing, margin, and overall deal health across the Enterprise pipeline Updates pricing and trend reporting to keep leadership current on where deals stand and how pricing is trending against targets Process Optimization Identifies bottlenecks in the deal review & approval process and proposes ways to accelerate cycle time Helps standardize and streamline recurring pricing/approval steps into repeatable, lower-friction workflows Tracks deal approval cycle time and surfaces trends to inform process improvements Cross-Functional Deal Coordination Owns deal crafting end-to-end from initial pricing/modeling through contract review, coordinating with sales management, reps, and internal stakeholders Ensures the relevant stakeholders (Accounting, Finance, EPD, Legal) review and approve deals at the appropriate stage before they progress Routes deal packages to the correct reviewers and tracks open items so deals aren't stalled waiting on sign-off Strategic & GTM Support Tackles ambiguous, open-ended questions around Scale's go-to-market motion and iterates quickly on solutions that deliver measurable results Supports Sales and Finance leadership in quarterly strategy and

Scale GP is Scale's enterprise Generative AI platform—APIs and infrastructure for knowledge retrieval, inference, evaluation, and intelligent automation. We power mission-critical workflows for leading enterprises, helping teams turn complex data and models into reliable, production-ready AI systems. We're building a new AI Enablement team to create the next generation of agent-powered tools that ground AI in real operational workflows. Our goal: help internal teams demystify their own workflows, then deploy agentic systems that reason over data, take action, and deliver measurable outcomes. We don't build in a vacuum. You'll use our own platform to solve real business problems internally—then selectively commercialize that same stack for customers. What we run on is what we sell. This is a 0→1 team. We're looking for a sharp, product-minded engineer who thrives in ambiguity, moves fast, and loves building systems from scratch alongside customers and cross-functional partners. You'll work closely with product, forward-deployed engineers, data scientists, and applied AI teams to turn real-world problems into scalable production solutions. If you like shipping fast, owning outcomes, and working across the stack—from polished frontends to distributed backends to LLM integrations—this role is for you. What You’ll Do Own full-stack features and projects end-to-end — from design through production deployment — within a larger product area Sample surfaces - Accounting Agents, Finance Copilots, GTM Agents, Agentic Experimentation Platforms Develop reliable backend services in Typescript/Python, work with distributed systems, data pipelines, and AI/ML infrastructure Integrate LLMs, vector databases, and agentic frameworks to power intelligent workflows Ship quickly through tight experimentation loops while maintaining high quality and reliability Adapt across the stack and learn new tools as needed to solve real problems end-to-end Ideal Experience 3+ years of full-tim

About the Team Merchant Analytics helps DoorDash make better product, business, and go-to-market decisions through high-quality analytics, predictive modeling, experimentation, and strategic thought partnership. We work across some of DoorDash’s most important merchant and marketplace priorities, building the measurement, insights, and decision frameworks that improve outcomes for merchants and drive company impact. About the Role We’re hiring two Data Science Managers, each to lead a pod within Merchant Analytics and help shape high-priority product and business decisions. In this role, you will lead a team of data scientists, partner closely with Strategy & Operations, Product, Engineering, and business leaders, and turn ambiguous questions into clear recommendations that influence roadmap and plan outcomes. Success in this role means building a high-performing team, raising the quality and speed of decision-making, and ensuring analytics work is tightly connected to measurable business impact. You will report into Director, Data Science on our Merchant Analytics team in our Analytics organization. You’re excited about this opportunity because you will… Lead and develop a team of data scientists responsible for high-impact analytics, predictive modeling, and decision support tied to DoorDash’s most important product, business, and GTM priorities. Partner closely with Strategy & Operations, Product, Engineering, and business leaders to shape decisions, influence roadmaps, and improve plan-critical metrics. Define success metrics, build measurement frameworks and predictive models, and use experimentation and analysis to connect product and operational levers to business outcomes. Build a high-performing pod that balances analytical rigor, strong prioritization, and clear storytelling in a fast-moving environment. Scale reusable analytics frameworks, tools, models, and best practices that make the broader organization more effective over time. We’re excited

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 The AI team is focused on one of Stripe’s most strategic growth areas: enabling the monetization and scaling of AI-native and AI-enabled businesses. We’re in a unique position – partnering with the world’s most ambitious AI companies (the likes of OpenAI, Anthropic, NVIDIA, etc) building on the frontier of artificial intelligence -- across infrastructure, foundation models, agents, and applications -- to help them grow and commercialize globally using Stripe’s full financial stack. As part of Stripe’s GTM / Sales organization, this team works closely with Product, Engineering, and Marketing to shape Stripe’s AI GTM strategy and ensure that the world’s leading AI companies -- from early-stage innovators to the largest public players -- choose Stripe as their monetization platform. What you’ll do Work with existing Stripe customers in the AI Industry to develop and execute long-term sales strategies to expand Stripe’s revenue Own the full sales cycle, from business case development, to deal structuring and negotiating, to close Develop account plans and cross sell into your list of strategic AI customers, driving growth through expansion and new revenue streams Drive deal strategy and commercial negotiations for large, complex renewals Develop relationships with executive stakeholders within your book of business, deeply understanding problems they are solving and helping drive to solutions Be responsible for account mapping and coor