Finance Business Partner in United States

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We are seeking a Senior Manager of Industrial Engineering to join CLEAR's Central Operations team. This role is the quantitative backbone of our Experience & Operations Design function — owning the data-driven design standards, labor models, and capacity planning that determine how CLEAR's physical operation is structured and staffed. You will be the analytical engine behind lane design decisions, engineered labor standards, and demand forecasts, ensuring the operation is designed to deliver a consistently excellent member experience efficiently at scale. What you'll do: Develop and own engineered labor standards and staffing models across CLEAR’s physical experiences, including Verifier, Greeter, eGate, Concierge, TSA PreCheck, Enrollment, Sports, and new programs, serving as the operations source of truth for labor and headcount inputs Define physical operating requirements and sizing standards across lane configurations, verification and enrollment experiences, hardware placement, and queue management; lead checkpoint design for new and existing airport locations Lead demand forecasting and capacity planning across CLEAR experiences, modeling throughput, staffing requirements, operating hours, and operational impact for new programs, launches, surge periods, and events Drive operational efficiency through time studies, process analysis, and labor optimization, identifying and developing opportunities to improve productivity, capacity, and the Member experience across the network Partner cross-functionally with Operations,

Instawork is on a mission to create meaningful economic opportunities for skilled hourly professionals in communities around the globe. Our AI-powered labor marketplace helps local businesses scale, and enables global technology companies to push the frontiers of robotics and AI. Backed by world-class investors like Benchmark, Spark Capital, Craft Ventures, Greylock, Y Combinator, and others, we’re looking for exceptional talent to reimagine the way the world works. We are looking for a highly organized, thoughtful, and execution-focused People Operations Manager to join our People team. This is a manager-level individual contributor role responsible for owning and continuously improving the core People operations that support our employees throughout their lifecycle. As we invest in how AI can improve the way we work, we are looking for someone who brings an AI-enabled mindset to People Operations—constantly looking for ways to simplify work, automate processes, and build more scalable employee experiences. Key Responsibilities People Operations & Employee Lifecycle Own the end-to-end employee lifecycle, including onboarding, employee changes, leaves, and offboarding, ensuring a seamless and high-quality employee experience. Manage and continuously improve People Operations processes, workflows, documentation, and internal resources. Serve as a primary point of contact for employees on People-related questions, policies, benefits, leaves, and workplace resources. Partner with Finance, IT, Recruiting, Legal, and other teams to ensure People processes and employee changes are executed accurately and on time. HRIS, Data & Compliance Own the day-to-day administration and data integrity of our HRIS, including employee records, job and compensation changes, and organizational data. Conduct regular audits and maintain People reporting to ensure data is accurate, complete, and compliant and to identify trends and opportunities for improvement. Support HR compliance

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Plaid's Recruiting Operations team exists to build and sustain the infrastructure, programs, and data that enable our recruiting organization to hire effectively, efficiently, and equitably. We drive operational strategy, systems implementation, data integrity, and process consistency across the full hiring lifecycle. In 2026, we are focused on scaling our coordination function, fully operationalizing Ashby as our ATS, and launching programs that raise the bar for recruiting effectiveness across Plaid. We are a lean, high-impact team, and we are growing. As the Recruiting Operations Coordinator at Plaid, you will sit at the intersection of recruiting coordination and operational program support. You will own white-glove scheduling for high-touch hiring pipelines, serve as the on-site RC presence in our San Francisco office, and act as a core member of the Recruiting Operations team -- contributing to the systems, tools, and processes that keep the function running. This is an entry-level program management role that flexes between recruiting coordination and operational program support -- the balance will shift based on hiring volume and team needs. You will be one of the first pe

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Our Payments Risk team builds and operates decisioning capabilities across Signal and Guarantee. We help customers tune thresholds and rules so they can approve more good transactions while reducing returns. For Guarantee, this work also protects the economics of the risk Plaid underwrites. You will be the technical, customer-facing Payment Risk Consulting Lead for Signal and Guarantee. You will interpret model outputs, diagnose customer performance, and turn that analysis into concrete threshold and rules recommendations. You will own proofs of concept and retros, improve existing integrations, and help the team identify patterns that can be scaled through better processes and product capabilities. Responsibilities Own customer proofs of concept and retros from analysis through recommendations and follow-through. Proactively optimize Signal customers, prioritizing accounts with high return rates. Read model outputs and diagnose the drivers of authorization and return-rate performance. Recommend threshold and rules changes that align with each customer's risk and authorization goals. Help Guarantee customers tune thresholds to achieve target authorization rates while protecting lo

About the Team OpenAI’s Healthcare team is working to ensure that advances in AI meaningfully improve health for everyone. We build AI systems that support patients, clinicians, and healthcare organizations while setting a high standard for deploying AI responsibly in a high-stakes domain. On the Healthcare team, we are building products and infrastructure that bring OpenAI’s capabilities into healthcare organizations and clinical workflows. We serve health care systems, insurance companies, and the broad range of healthcare IT companies. Our products include connecting ChatGPT with healthcare data and systems and building reliable enterprise experiences that can operate within complex security, privacy, compliance, and interoperability requirements. We work closely with product, research, design, security, privacy, GTM, and our healthcare customers to turn powerful AI capabilities into dependable products that clinicians and healthcare organizations use in their everyday work. About the Role We are looking for backend and full-stack software engineers to build the systems behind OpenAI’s healthcare products. You will work across backend services, APIs, data systems, integrations, and product surfaces to connect AI with healthcare workflows and enterprise data. You’ll tackle the technical challenges involved in making these systems secure, reliable, observable, and scalable enough for real-world healthcare environments. This is a product-engineering role for someone who can move between customer problems and complex system architecture, and who is comfortable owning ambiguous problems end-to-end. In this role, you will: Design and build backend and full-stack systems powering OpenAI’s healthcare products. Build services, APIs, and data pipelines that connect OpenAI products with healthcare systems and enterprise data. Develop integrations with electronic health records and other healthcare data sources. Design systems that meet demanding requirements around privacy,

About the Team The Cooperative AI team is scaling OpenAI with OpenAI. We are building a model-powered scaled automated workforce and knowledge system that evolves and learns alongside a human workforce. By leveraging OpenAI’s state-of-the-art models and technologies, some already in production, others still in the lab, we develop systems that reason and work autonomously for a wide variety of operational work. We leverage real workloads for critical systems across finance, sales, customer support, integrity, product insights, internal operations, and more in order to drive insights into product and industry. We partner closely with internal teams and external customers globally, operating in a hyper-fast feedback loop where many of our users are just a few steps away. This proximity allows us to iterate quickly, validate impact in real time, and accelerate industry impacting learnings and systems builds. We are a highly multidisciplinary, self-contained team focused on transforming the workplace via smart systems, knowledge, scalable and reliable primitives that apply world-class AI capabilities across domains. Our mission is to learn fast and transform how humans collaborate with AI at scale. About the Role We are looking for a hands-on Engineering Manager to lead a small, fast-moving team building AI-powered automation systems that redefine how work gets done across OpenAI. This role sits at the intersection of applied AI, research, and product engineering. You’ll lead a team that builds systems that know how to learn from humans, and carry real workloads across, sales, support, finance, IT, and more, while staying deeply involved in the technical work. You will operate in a highly iterative environment, deploying systems directly to internal users, gathering rapid feedback, and evolving solutions in real time. This is a high-ownership role for someone excited about building 0→1 systems, working closely with customers, and shaping how AI transforms operational wor

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. The Fraud Data team at Plaid builds the machine learning systems that power Plaid’s fraud detection products, leveraging insights from across Plaid’s network to help identify and stop fraud before it happens. Our team works across the full data science and machine learning lifecycle—from discovering new signals and experimenting with models to deploying and optimizing them in production. We continuously learn from real-world model performance and customer feedback to improve our systems and develop new ways to protect customers and consumers from evolving fraud threats. As a Senior Machine Learning Engineer on Plaid's Fraud Data team, you will develop models that improve fraud detection for our customers. You will identify predictive patterns in Plaid's network data and lead projects from initial experiments through model deployment and ongoing improvement. Investigate fraud patterns and model errors to identify new signals, improve detection, and expand coverage across customers and use cases. Develop training datasets and predictive features, addressing challenges such as incomplete labels, class imbalance, data leakage, and changing fraud behavior. Design, train, and tune model

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. We are the Fraud Data team within Plaid's Fraud organization. We leverage relationships and activity across Plaid’s network to develop machine learning models that help customers detect and prevent fraud while minimizing friction for legitimate users. Our team owns the full model lifecycle, from data processing and experimentation to feature pipelines, model serving, and monitoring. In this research role, you’ll partner closely with Machine Learning Engineers and Data Scientists to uncover new signals, explore and evaluate innovative modeling approaches, and translate promising research into production-ready solutions that strengthen fraud detection across Plaid’s network. As a Senior Research Scientist, you will lead applied research to develop next-generation fraud detection models across relational graphs, sequential events, images, and video data. You’ll design rigorous experiments and evaluation methodologies that reflect real-world fraud dynamics, while exploring state-of-the-art approaches such as Graph Neural Networks and Transformer-based foundation models. In close partnership with Machine Learning Engineers, you’ll translate promising research into production-ready solu

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Fraud Data is the data science and machine learning team within Plaid’s Fraud organization, responsible for using data and ML to improve and scale Plaid’s fraud products. Within Fraud Data, the Customer & Product Intelligence team focuses on understanding product performance, uncovering customer insights, and enabling go-to-market teams with data-driven solutions. The team partners closely with customers and GTM teams on fraud analyses and proofs of concept, turning customer learnings into scalable, reusable product capabilities. We also build the metrics, analytics, and data foundations that measure product health, identify opportunities for improvement, and guide product decisions across Plaid’s Fraud portfolio. As a Data Science Manager, you will lead a team responsible for customer-facing data science and Fraud product analytics. You will set the team's roadmap, develop its data scientists, and remain involved in analytical methods, technical reviews, and customer investigations. You will: Set a 6–12-month roadmap with Product, Engineering, and GTM, and assign priorities and responsibilities across the team. Define product metrics, their underlying data, and reporting and

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. We are the Data team within Plaid’s Fraud organization. We build the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s network data to help identify and prevent fraud before it happens. Our team owns the end-to-end ML lifecycle, from feature pipelines and model training to production serving and monitoring, ensuring our systems are reliable, scalable, and built to support hundreds of customers and data partners. As a Data Scientist on the Fraud Data team, you will analyze customer and network traffic to understand how Plaid Protect performs across a range of use cases and customer segments. You’ll build dashboards and metrics that provide a clear, shared view of product performance, run backtests to evaluate performance and identify high-impact rules and model strategies, and generate insights that support customer growth and expansion. You’ll also design scalable data models and schemas to enable reliable analysis and reporting, while partnering closely with Product and Engineering to design and analyze experiments for new customer-facing features. Responsibilities: Work at the intersection of product analytics, machine learning, and fraud a

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. The Data team within Plaid’s Fraud organization builds the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s unique network data to identify and stop fraud before it happens. The team owns the full ML lifecycle—from feature pipelines and model training to production serving and monitoring—building reliable, scalable systems that deliver high-quality fraud detection as we grow to support hundreds of customers. As a Senior Machine Learning Engineer, you will own the development of high-performance feature computation and online inference pipelines that power production machine learning systems at scale. You’ll build robust observability, monitoring, and automated debugging capabilities, while leveraging AI-assisted tools to investigate complex system behavior and maintain high reliability. You’ll partner closely with ML Infrastructure, Data Science, and Product teams to execute critical technical initiatives and deliver scalable, high-impact ML solutions. Responsibilities: Build and scale machine learning systems that power a rapidly growing fraud detection product in a fast-paced environment. Solve complex technical challenges at the intersect

About the Team OpenAI's Industrial Compute organization builds and operates the infrastructure required to train and serve frontier AI models. The Capacity Planning team connects rapidly changing research and product demand with the compute, networking, storage, power, data center, hardware, and operational resources required to make that demand executable. About the Role We are seeking a Technical Program Manager to build and lead capacity planning across OpenAI's large-scale AI infrastructure. You will translate uncertain workload demand into clear infrastructure requirements, allocation decisions, supply commitments, activation priorities, and long-range capacity strategies. This role sits at the intersection of research, engineering, infrastructure, finance, sourcing, deployment, and operations. You will create the planning models, operating cadences, governance mechanisms, and source-of-truth systems that allow teams to understand what capacity is required, what is available, what is at risk, and what decisions must be made. This is not a finance-only forecasting or reporting role. Success requires technical fluency across the infrastructure stack, strong analytical judgment, and the ability to move consequential decisions forward when requirements, timelines, and supply conditions change quickly. Key Responsibilities Own capacity-planning processes across near-term workload allocation, quarterly execution, and longer-range infrastructure horizons. Translate research, training, inference, and product demand into compute, accelerator, cluster, networking, storage, rack, power, and site requirements. Develop scenarios that make assumptions, confidence levels, constraints, sensitivities, and decision points explicit. Reconcile requested demand against contracted, delivered, installed, activated, and workload-usable capacity. Partner with research and engineering teams to understand workload priorities, technical dependencies, utilization patterns, and changing req

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. About the Team At Embedded Insights, we find the best machine learning opportunities for external products and internal systems, and collaborate with cross-functional partners to bring them to life. We are a central team of Machine Learning Engineers and Data Scientists. We embed with partner teams to build and apply machine learning models that improve internal decision-making and power the Plaid product suite. About the Role You will be the first Data Scientist on the Embedded Insights team, part of Plaid’s Data organization. You will establish the analytics and metrics backbone for a team supporting a diverse set of internal and external products. You will help drive better decision-making, support machine learning model development, and contribute directly to the health of the Plaid network and the quality of Plaid’s products. Your day-to-day work will include: Analyzing entities across the Plaid network to understand behavior and identify opportunities, anomalies, and risks. Creating foundational metrics, dashboards, and monitoring systems that provide a clear view of network health and machine learning model performance. Evaluating the value and performance of machine learni

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE As a member of the Capacity Strategy & Operations team, you will sit at the intersection of supply intelligence, demand forecasting, and cross-functional execution, turning a complex, fast-moving hardware market into a predictable, reliable foundation for our customers and internal engineering teams. This is not a purely analytical role. You will own the end-to-end capacity planning process: from translating customer commitments and growth forecasts into concrete supply requirements, to coordinating fulfillment across vendors, finance, and the infrastructure team, to building the systems that make all of this repeatable and scalable. When supply is constrained and tradeoffs are unavoidable, you are the person in the room who can model the options, make a clear recommendation, and drive alignment fast. You are a strong fit if you have operated at the intersection of strategy and execution before — someone who is equally comfortable building a capacity model in a spreadsheet and running a cross-functional war room when a customer deployment is at risk. EXAMPLE INITIATIVES Demand-Supply Alignment Framework: Build and own the process that translates customer pipeline, signed commitments, and growth projections into a forward-looking GPU demand signal — so the team is never caught flat-footed when a customer scales faster than expected. Constrained Allocation Playbook: Define the decision framework for how Basete

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. About the Team The Workplace Experience (WPE) team is responsible for shaping the employee experience at Plaid, ensuring that our workspaces, events, and cultural touchpoints drive connection, collaboration, productivity, and engagement. Within WPE, the Events & Experiences team brings Plaid's culture to life by designing and executing programs that foster belonging and engagement across both in-office and distributed environments. The team curates a wide range of experiences—from flagship company-wide gatherings to in-office celebrations, DEIB initiatives, virtual events, and milestone moments. They also lead Plaid's in-person onboarding, ensuring every new hire has a meaningful, high-impact introduction to our culture, values, and ways of working. About the Role We're looking for an Onboarding Coordinator to join our Employee Experience team in San Francisco. You'll help create a warm and seamless welcome for new Plaids by coordinating onboarding logistics, supporting new-hire travel, answering questions, and assisting with in-person sessions. You'll also support employee events and programs that help Plaids feel connected, valued, and engaged. What You'll Do Onboarding Help