Data Scientist

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role We’re looking for someone to help lead the future of analytics at Ramp. This person will enable Ramp to get 1% better every day by developing data products and insights. They will partner closely with business stakeholders and product, engineering, and design counterparts to prioritize and execute on work, improve reporting, as well as drive results and process improvements. What You’ll Do Full stack development, building models to consume, transform, and expose data to stakeholders and production systems Drive a culture of experimental design, testing agenda, and best practices Contribute to the culture of Ramp’s data team by influencing processes, tools, and systems that will allow us to make better decisions in a scalable way Collaborate with P/E/D/D (product, engineering, data and design) teams to develop product roadmaps and measure success Work closely with data engineering teams to capture, move, store, and transform raw data into highly actionable insights, and partner with business teams to turn those insights into action Wha

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Data Scientist What is the opportunity? We are seeking a highly skilled and motivated Data Scientist to join our Cyber Analytics team within the Security Solutions Data Science organization. This role is critical to driving advanced analytics initiatives, improving fraud detection capabilities, and supporting strategic decision-making across cybersecurity and payment fraud domains. What will you do? • Gain subject matter knowledge on web application security, commonly exploited cyber vulnerabilities, and methods of online and payment card fraud including the common points of purchase for compromised cards. • Build, develop, and maintain innovative data-driven analytical solutions, including predictive models and machine learning algorithms, on large volumes of data to support analytics and reporting needs across products, markets, and services. • Competently handle large datasets, sifting for patterns and trends and translating those insights into technical rules and solutions. • Combine cybersecurity and transaction data into new and insightful views of fraud and vulnerability across the Mastercard network. • Collaborate with cross-functional teams including product, engineering, and operations to understand product, usage, and data pipelines as well as delivering scalable solutions. • T

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. What You’ll Do Full stack development, building models to consume, transform, and expose data to stakeholders and production systems Drive a culture of experimental design, testing agenda, and best practices Contribute to the culture of Ramp’s data team by influencing processes, tools, and systems that will allow us to make better decisions in a scalable way Collaborate with Finance teams (e.g. GTM Finance, StratFin) to develop financial insights and influence business decisions Work closely with data engineering teams to capture, move, store, and transform raw data into highly actionable insights, and partner with business teams to turn those insights into action What You Need Minimum of 3 years of industry experience in Data Science / Software Engineering / Finance Strong AI proficiency as a lever to quickly adopt new skills and subject matter Track record of shipping high quality products and features at scale Ability to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical so

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role We’re looking for a Senior Applied Scientist to help drive the future of credit applied science at Ramp. In this role, you will design, build, and optimize the models that power our credit risk systems, helping us make faster, smarter, and more scalable risk decisions for our customers. You’ll work at the intersection of machine learning, statistics, economics, and product strategy. This role requires strong technical depth as well as close collaboration with business, product, data, and engineering partners. You will help identify high-impact opportunities, translate ambiguous business problems into rigorous modeling work, and ship models that operate reliably in production. Applied scientists at Ramp focus on solving quantitative problems across credit, fraud, growth, and our core product by applying the right mix of machine learning, causal inference, structural modeling, and optimization. What You'll Do Design, build, and optimize machine learning models that support credit risk decisioning and portfolio management at Ramp Own the

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role The Data Platform builds infrastructure and tools that enable Ramp to realize business value from data. We partner closely with stakeholder teams to build this infrastructure and the applications on top of it. This role is particularly focused on building platforms that support the data science development lifecycle. You’ll partner with applied scientists, AI engineers, Risk engineers, and other ML developers on building infrastructure and tools that enable and accelerate the development of machine learning models. What You’ll Do Build and integrate the components of Ramp's Analytics Platform and Machine Learning Platform. Build tools that improve the agility and data experience of Ramp's Applied Scientists, AI Engineers, and Risk Engineers. Collaborate with stakeholder teams on building and productionizing machine learning applications. Build reliable, scalable, maintainable, and cost-efficient systems across the stack. What You Need Experience with workflow orchestrators like Airflow, Dagster, or Prefect. Experience building infrast

About Pinecone Pinecone is the knowledge infrastructure for AI at scale. Its leading vector database and knowledge engine, Pinecone Nexus, power accurate, performant AI applications for more than 9,000 customers and 800,000 developers worldwide. Pinecone's mission is to make AI knowledgeable. Pinecone is based in New York and raised $138M in funding from Andreessen Horowitz, ICONIQ, Menlo Ventures, and Wing Venture Capital. About the Team and Role: We are hiring a senior/staff software engineer to help design and build core components of our next-generation knowledge retrieval system built for the AI era – search and retrieval infrastructure that powers high-quality, scalable, and enterprise-grade agentic systems. You’ll build the framework that allows our customers to connect knowledge–synthesized from structured and unstructured data–to modern LLM-powered applications, leveraging the world’s best-in-class vector DB supporting semantic search and hybrid retrieval. This role is ideal for someone who loves backend system architecture, distributed systems, and applied AI infrastructure. It is a high impact role with significant ownership across architecture, performance, and system reliability. Responsibilities: Design and build scalable platform components leveraging advanced retrieval via query planning, semantic and hybrid search, metadata-aware search, and LLM generation Design and build optimized indexing pipelines for structured and unstructured data Build backend services for semantic and hybrid retrieval, knowledge graph construction, and retrieval orchestration Improve retrieval quality through evaluation and observability frameworks Design APIs for internal and external user and agentic consumers Optimize latency, throughput and cost across large-scale inference and retrieval workloads Drive technical direction for reliability and security What You’ll Bring to the Table: To thrive in this role, you don't need to check every single box, but you should be deep