Data Client Onboarding Specialist in United States

About the Team OpenAI’s Financial Engineering (FinEng) team powers how revenue flows through our products—pricing & packaging, checkout, payments, subscriptions, and the financial infrastructure behind them. We partner with Product, Engineering, Risk, Finance, and Go-to-Market to make paying for OpenAI products seamless, reliable, and efficient worldwide. About the Role As a Data Scientist on FinEng, you’ll own the analytics and experimentation that improve our checkout and payments , subscriptions , and pricing & monetization systems. You’ll define the metrics that matter, build the source-of-truth data assets, and design experiments that increase conversion, reduce churn and payment failures, and expand global payment method coverage. Your work will directly influence revenue, customer experience, and how we scale internationally. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will Own checkout & payments analytics and experimentation across methods and locales (e.g., bank transfers, emerging rails), improving conversion while monitoring risk and latency. Build and run the experimentation program for in-house checkout—define success metrics and guardrails, execute staged rollouts, and use offline incrementality when online tests aren’t feasible. Create operational visibility and source-of-truth data with FinEng Data Engineering—land team-level metrics, SLAs, and self-serve dashboards that drive proactive action. Lead subscription, retention, and monetization analytics—ship launch-readiness for new subscription features, reduce involuntary churn (e.g., targeted retrials/nudges), and develop elasticity/FX frameworks toward pricing optimality. You might thrive in this role if you have 5+ years in a quantitative role (data science, product analytics, or experimentation) in high-growth or fintech environments Fluency in SQL and Python ,

About the Team OpenAI is building the infrastructure foundation for the next generation of AI. The Data Center Engineering team defines the strategy, reference architectures, technical requirements, and delivery standards for the large-scale data centers that support OpenAI research, products, and infrastructure partners. As a Data Center Infrastructure Electrical Engineer, you will help define, validate, and scale the electrical power systems that support high-density AI compute. You will translate evolving compute requirements into practical facility and rack-power architectures, evaluate new technologies and vendor solutions, and drive technical decisions across design, manufacturing validation, construction, commissioning, deployment, and operations. This role is best suited for a senior hands-on engineer with deep experience in mission-critical power systems, strong judgment under ambiguity, and the ability to connect facility infrastructure, hardware requirements, controls, telemetry, reliability, and operations. About the Role We are seeking a senior electrical infrastructure engineer to lead the development of reliable, scalable, and efficient power architectures for high-density, liquid-cooled AI data centers. The ideal candidate has strong practical experience with critical electrical systems at data centers or comparable industrial scale, including medium-voltage and low-voltage distribution, utility interfaces, backup power, UPS and battery systems, rack power delivery, grounding, protection, controls, and monitoring systems. You should be comfortable moving between long-range architecture, detailed engineering review, lab validation, vendor qualification, field deployment, and operational troubleshooting. Key Responsibilities Design and optimize electrical topologies and equipment strategies that reduce cost, accelerate schedules, improve efficiency, increase scalability, and maintain high reliability and maintainability. Review and develop basis-of-des

About the Team The Strategic Finance team at OpenAI plays a critical role in shaping the company’s long-term trajectory. We partner closely with Product, Engineering, and Go-To-Market teams to inform high-stakes decisions through rigorous data science and economic modeling. As part of our expanding Data Science function, we’re building a best-in-class Forecasting capability to drive real-time, data-driven decision-making across user growth, revenue, compute infrastructure, and more. We are developing scalable forecasting infrastructure to help us understand and anticipate business dynamics in an increasingly complex, usage-based world. Our models are foundational to planning, pricing, operational efficiency, and growth strategy - supporting key investment decisions and unlocking OpenAI’s full potential. About the Role We’re looking for a senior Machine Learning Data Scientist to lead our forecasting initiatives. You’ll be one of the founding members of the Forecasting pillar within Strategic Finance Data Science, responsible for building and scaling robust, interpretable, and production-ready forecasting systems. Your models will power critical business decisions by predicting core metrics such as DAU/WAU, revenue, LTV, compute consumption, and profitability. This is a highly cross-functional role, requiring technical excellence, strong product intuition, and business acumen. You’ll collaborate with product managers, researchers, engineers, and finance leaders to operationalize forecasting insights, influence company-wide strategy, and build foundational forecasting capabilities at OpenAI. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Build statistical and machine learning models to solve forecasting needs across product, finance, infrastructure, and GTM domains. Own the end-to-end modeling lifecycle , including scoping, feature engineerin

About the Team OpenAI’s Platform team powers how millions of developers and enterprises build with our models. We provide APIs and agentic solutions used by global startups and fortune 500s. We work closely with product, engineering, design, and go-to-market to build a world-class platform that pushes the frontier of AI capabilities. About the Role As a Data Scientist on the Platform team, you will drive a data-driven culture for OpenAI’s API and B2B solutions. You’ll define the metrics that matter for developer success and enterprise value, measure the impact of new models and features, and partner with PMs and engineers to improve model quality, reliability, latency, and cost. Your work will shape how thousands of products adopt agentic AI. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will Embed with the Platform product team as a trusted partner, uncovering ways to improve developer experience, reliability, and usage growth Define north-star metrics across the developer funnel (activation, retention, growth), as well as latency/cost guardrails for new features and models Design and interpret A/B tests and controlled rollouts (e.g., new model versions, pricing/limits, new API features, new B2B products) Build source-of-truth dashboards and self-serve data tools for product, engineering, and go-to-market teams Translate product learnings into actionable feedback for Research (e.g., failure modes, eval gaps, model response quality) You might thrive in this role if you have 5+ years in a quantitative role in ambiguous, high-growth environments (platforms, APIs, or B2B products a plus) Depth in SQL and Python, with a track record proposing, designing, and running rigorous experiments Experience defining and operationalizing metrics from scratch (including reliability/latency/cost and safety) Strong cross-functional communication with PMs, enginee

Job Description: Data Scientist, B2B Demand Generation, Growth & Measurement About the Role We are hiring a Data Scientist to lead measurement, experimentation, and decision science for B2B marketing demand generation. You will help us understand which marketing investments create incremental demand, qualified pipeline, and revenue and how to scale them efficiently. Our mandate is to build a rigorous, full-funnel view of how B2B marketing creates demand and moves prospects from awareness and engagement to qualified opportunities, closed-won revenue, and expansion. You will shape how we measure marketing impact and influence across channels, campaigns, audiences, and account segments. In this role, you will partner closely with B2B Marketing, Demand Generation, Growth, Sales, RevOps, Finance to connect marketing activity to qualified pipeline, customer acquisition, and efficient revenue growth. What You’ll Do Define north-star, leading, and guardrail metrics for B2B demand generation, including account engagement, qualified leads and opportunities, sourced and influenced pipeline, conversion rates, pipeline velocity, and incremental ARR. Design and execute measurement and experimentation strategies across channels and campaigns, using randomized tests, audience or geographic holdouts, lift studies, quasi-experimental methods, and other causal approaches suited to long B2B sales cycles. Analyze channel, audience, campaign, creative, content, landing-page, and account-segment performance to identify the drivers of qualified demand, funnel conversion, pipeline quality, and incremental revenue. Partner with Marketing, Sales, RevOps, Finance, Product, and Engineering to improve instrumentation, campaign taxonomy, CRM data quality, lead-to-account matching, and the operating cadence for acting on measurement insights. Build AI-native measurement and decision-support workflows, using LLMs and agents to synthesize campaign performance, surface growth opportunities, and h

About the Team The Preparedness team is an important part of the Safety Systems org at OpenAI, and is guided by OpenAI’s Preparedness Framework . Frontier AI models have the potential to benefit all of humanity, but also pose increasingly severe risks. To ensure that AI promotes positive change, the Preparedness team helps us prepare for the development of increasingly capable frontier AI models. This team is tasked with identifying, tracking, and preparing for catastrophic risks related to frontier AI models. The mission of the Preparedness team is to: Closely monitor and predict the evolving capabilities of frontier AI systems, with an eye towards misuse risks whose impact could be catastrophic to our society Ensure we have concrete procedures, infrastructure and partnerships to mitigate these risks and to safely handle the development of powerful AI systems Preparedness tightly connects capability assessment, evaluations, and internal red teaming, and mitigations for frontier models, as well as overall coordination on AGI preparedness. This is fast paced, exciting work that has far reaching importance for the company and for society. About the Role We’re hiring a Data Scientist to help build, evaluate, and continuously improve mitigations that prevent extreme harms from AI systems. This role is for an experienced, highly autonomous individual contributor who can take ambiguous problem statements, structure rigorous analyses, and translate findings into actionable product and policy changes. This position goes beyond “running evals.” You’ll help create mitigation intelligence and monitoring systems that enable OpenAI to detect issues early, measure effectiveness over time, and reduce both over-blocking (unnecessary friction) and under-blocking (missed harm). What You’ll Do Evaluate and improve mitigation systems, including classifiers and detection pipelines across domains (e.g., biosecurity, cybersecurity, and emerging risk areas). Diagnose false positives and fa

About the Team OpenAI is building the infrastructure foundation for the next generation of AI. The Data Center Engineering team defines the strategy, reference architectures, technical requirements, and delivery standards for the large-scale data centers that support OpenAI research, products, and infrastructure partners. As a Data Center Infrastructure Engineering Program Manager, you will help turn complex infrastructure strategy into executable programs across electrical, mechanical, controls, network, hardware, construction, commissioning, deployment, and operations workstreams. You will partner with research, hardware engineering, data center engineering, site development, supply chain, security, EHS, finance, legal, operations, and external delivery partners to bring OpenAI's infrastructure vision to life. About the Role We are looking for an Engineering Program Manager (EPM) to lead assigned infrastructure programs focused on production and non-production network integration, controls coordination, and the design and deployment of data hall or whitespace facilities. The EPM will support functional Directly Responsible Individuals (DRIs) across network, controls, structural, electrical, and mechanical disciplines. Key responsibilities include coordinating assigned workstreams and program controls, maintaining risks and interfaces, and supporting readiness within the network and data hall deployment track. The ideal candidate thrives on bringing structure to complex environments characterized by ambiguous technical requirements, large partner ecosystems, tight deadlines, and high operational stakes. This individual must be adept at keeping teams aligned on decisions, risks, dependencies, schedules, and readiness criteria, and escalating gaps or decision points when needed. Candidates should have a proven track record of managing technically challenging engineering programs across major lifecycle phases, including design, validation, procurement, construction, c

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary The Senior Data Engineer will be responsible for delivering high quality modern data solutions through collaboration with our engineering, analysts, data scientist, and product teams in a fast-paced, agile environment leveraging cutting-edge technology to reimagine how Healthcare is provided. You will be instrumental in designing, integrating, and implementing solutions on-premise as well supporting migrations of existing workloads to the cloud. The Senior Data Engineer is expected to have extensive knowledge of modern programming languages, designing and developing data solutions. The position is open in a data engineering team that is responsible for processing payer files into our Data Warehouse. Required Qualifications 6&#43; years of experience working with SQL and relational database management systems 3&#43; years of experience in Cloud Data Engineering Platforms such as AWS, GCP, Azure, Databricks, Snowflake etc. 3&#43; years of experience in on-prem Data Engineering Platforms such as Microsoft SQL Server, Oracle, Teradata etc. Programming and modifying code in languages like SQL, Python, and PySpark to support and implement Cloud based and on-prem data warehousing services.</spa

The pay range is $132,000.00 - $238,000.00 Pay is based on several factors which vary based on position. These include labor markets and in some instances may include education, work experience and certifications. In addition to your pay, Target cares about and invests in you as a team member, so that you can take care of yourself and your family. Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves. Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation. Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits . JOIN TARGET AS A LEAD DATA SCIENTIST – RECOMMENDATIONS (RecSys) About Us: Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here <span style="color:#00

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. POSITION SUMMARY CVS Health is seeking a highly skilled Staff Data Engineer, Observability Engineering to join the Enterprise Observability Platform organization and help advance the next generation of observability, infrastructure, and security data capabilities. The Staff Data Engineer, Observability Engineering will play a critical role in designing, building, and operating scalable data pipelines and data products that power enterprise observability, operational intelligence, and security analytics across the organization. The Staff Data Engineer, Observability Engineering is a senior individual contributor responsible for developing and optimizing Databricks-based data engineering solutions that ingest, transform, govern, and deliver high-volume telemetry, infrastructure, application, and security data. This role combines deep hands-on technical execution with ownership of engineering excellence, operational reliability, performance optimization, and data platform best practices. Working closely with Observability Engineering, Security Engineering, Infrastructure Engineering, and Data Platform teams, the Staff Data Engineer, Observability Engineering will contribute to the evolution of the enterprise observability lakehouse by building resilient ingestion frameworks, establishing data quality standards, enhancing governance controls, and driving efficient, scalable data processing patterns. The id

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary The growing DSNP business has created an opportunity for an individual with claims experience, who is familiar with the 837 standard claims format. This individual will own 837 file transmissions to the states, manage and act on state response files, ensuring that all transactions transmitted are complete and error free. Manage and complete error corrections to meet state requirements. Required Qualifications 1&#43; year of experience with encounter data, medical claims, or Medicare/Medicaid. 1&#43; year of experience using FTP and data transfer software. 1&#43; year of data management experience. Preferred Qualifications Experience with Microsoft Access Databases. Analytical skills with the ability to identify and resolve data discrepancies. Working knowledge of the 837 claims files. Education Bachelors degree or equivalent work experience Anticipated Weekly Hours 40 Time Type Full time Pay Range <p s

NVIDIA is a global leader in high-speed computer vision, artificial intelligence (AI), and deep learning. Our team develops data engineering solutions that empower AI developers in autonomous vehicle (AV) domains to innovate quickly and effectively at scale. Are you ready to take on a senior technical role in building high-performance AI data pipelines? We seek an exceptional individual to design and optimize microservices and data pipelines to process massive volumes of AV data and enable seamless data mining and AI training. The ideal candidate will bring expertise in big data processing and distributed computing to create efficient solutions and overarching architectures for challenges such as video data curation, behavioral search, and AI dataset management. What you'll be doing: Scope and build tools, microservices, workflows, and distributed applications to accelerate data mining and AI training. Design and implement solutions for streaming, resilience, logging, security, authentication, workflow orchestration, and data management. Deploy AI models. Design and develop Retrieval-Augmented Generation (RAG) workflows enabling hybrid and agentic patterns. Analyze and operationalize complex distributed systems for speed-of-light performance. What we need to see: Experience developing high-performance, scalable software systems. MS with 6&#43; years, or BS (or equivalent experience) with 8&#43; years of relevant experience in Computer Science, Computer Engineering, or a related technical field. Strong programming skills in Python or Golang Proficiency in key technologies like Kubernetes, Helm, Hive, Parquet, SQL, vector databases, e.g., Milvus. Strong architectural skills with a proactive, problem-solving mentality. Experience in data mi

What if the work you did every day could impact the lives of people you know? Or all of humanity? At Illumina, we are expanding access to genomic technology to realize health equity for billions of people around the world. Our efforts enable life-changing discoveries that are transforming human health through the early detection and diagnosis of diseases and new treatment options for patients. Working at Illumina means being part of something bigger than yourself. Every person, in every role, has the opportunity to make a difference. Surrounded by extraordinary people, inspiring leaders, and world changing projects, you will do more and become more than you ever thought possible. Summary The Staff Data Engineer is a seasoned, hands-on engineer who designs, builds, and scales data products on our cloud lakehouse, powering analytics, reporting, and AI/ML across Illumina. We are looking for someone with strong proficiency in Python, SQL, and data modeling, a solid understanding of distributed systems and system design who has built and scaled data products on modern cloud platforms such as Databricks and Snowflake. This is a hands-on, senior individual-contributor role with end-to-end ownership and leadership spanning multiple domains such as Supply Chain, Manufacturing and Quality, including mentoring engineers on our global (India-based) team. Responsibilities Partner across business, AI, and platform teams translating domain needs (e.g., SAP, Manufacturing, Quality) into well-modeled, governed and scalable data products. Design, build, and scale end-to-end data products on Databricks (and interoperating with Snowflake) — from ingestion through curated, analytics-ready datasets following a medallion (Bronze/Silver/Gold) architecture. Develop reusable frameworks, libraries, and

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary Designs, builds, and maintains large-scale data infrastructure and data processing systems. Implements robust and scalable solutions to support data-driven applications, analytics, and business intelligence. What you will do Ensures seamless integration of data from different sources, such as databases, application programming interfaces (APIs), or streaming platforms. Optimizes data processing and query performance by fine-tuning data pipelines, database configurations, and data partitioning strategies. Establishes data quality checks and validations to identify and resolve data issues, ensuring high-quality and reliable data for downstream applications and analytics. Implements security measures to protect sensitive data throughout the data lifecycle by working closely with security teams to ensure data encryption, access controls, and compliance with data protection regulations. Collaborates with cross-functional teams, including data scientists, analysts, software engineers, and business stakeholders. Designs and develops data infrastructure, including data warehouses, data lakes, and data pipelines. Establishes auditing and monitoring mechanisms to track data access and maintain data governance standards. Establishes monitoring and alerting mechanisms

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. Position Overview: The Cyber Security team at Freddie Mac is searching for a strong data analyst to collaborate on developing and administering data security policies as well as safeguarding information, evaluating existing data security procedures and identifying new areas of risk for Freddie Mac. If this role sounds like a fit for your skill set, please read on, apply and learn why there is #MoreatFreddieMac ! Our Impact: We develop and train the enterprise on relevant Identity and Access Management best practices, develop and support automated IAM processes, and develop and implement ongoing IAM efficiency improvements with limited oversight by managers. The role will work closely with Enterprise partners and security control owners on IAM automation development activities and alignment of IAM processes with InfoSec maturity targets as described in the InfoSec Strategy. Your Impact: Senior Data Analyst who can develop and implement new and updated business process automation for all Identity and Access Management activities. Develop and proposes strategies to reduce security risk in the organization by implementing procedural prevention, detection, and response measures, while still enabling positive business outcomes. Comfortable supporting ad hoc data retrieval and analysis requests using SQL queries and Copilot/Excel . Creating audit-ready reference documentation. This role will allow for and support rapid AI-based extrapolation/replication of these services as future automated IAM microservices. Qualifications: Typically, 5 - 7 years of rel