Quantitative Analytics And Model Analyst Senior in United States

Position Overview At PNC, our people are our greatest differentiator and competitive advantage in the markets we serve. We are all united in delivering the best experience for our customers. We work together each day to foster an inclusive workplace culture where all of our employees feel respected, valued and have an opportunity to contribute to the company’s success. As a Quantitative Analytics and Modeling Analyst Senior within PNC's Model Risk Management organization, you will be based in Pittsburgh, PA, Boston, MA or Tysons Corner, VA. We are seeking an experienced model validator to be part of our Model Risk Management team at PNC. The position reports to a validation manager in Commercial Credit and Financial Valuation Models and is part of the Independent Risk Management organization. This role involves performing rigorous independent reviews on some of PNC’s most important models including Commercial & Industrial, Commercial Real Estate and retail commercial loss forecasting models, risk rating models, as well as financial valuation and investment models. This role also participates at and provide individual and aggregate model risk assessment in various model working groups and forums. PNC is an in-office company that fosters a supportive culture

About Flexport: At Flexport, we believe global trade can move the human race forward. That’s why it’s our mission to make global commerce so easy there will be more of it. We’re shaping the future of a $10T industry with solutions powered by innovative technology and exceptional people. Today, companies of all sizes—from emerging brands to Fortune 500s—use Flexport technology to move more than $19B of merchandise across 112 countries a year. The recent global supply chain crisis has put Flexport center stage as we continue to play a pivotal role in how goods move around the world. We are proud to have the support of the best investors in the game who believe in our mission, solutions and people. Ready to tackle global challenges that impact business, society, and the environment? Come join us. The Opportunity We're looking for an Analyst who thrives at the intersection of transportation economics, supply chain strategy, and quantitative modeling. This is a high-visibility individual contributor role—you won't be managing people, you'll be doing the work that directly shapes our network design, carrier strategy, and cost structure. In this role, you will not just build models, but proactively identify high-impact cost-saving and optimization opportunities, transforming raw analysis into business-critical strategy.Your analysis will inform senior leadership decisions on carrier RFPs, zone skip expansion, FC location strategy, and how we price and position our fulfillment product against competitors. You'll partner closely with carrier ops managers, supply chain leadership, data science, and commercial teams to turn complex data into clear, actionable recommendations. You Will Own lane analysis and zone skip strategy including lane-level margin modeling, utilization thresholds, go/no-go decision frameworks for trailer dispatch, and identification of new lane opportunities across our middle mile and deep injection network. Drive Cross-Functional Execut

As a Senior Deal Desk Analyst, you will work cross-functionally with our Sales Operations, Billing, Contracts and Legal teams to provide quoting and deal structuring support to the Global Sales Team. This will be a growth position as Datadog’s business continues to expand. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them What You’ll Do: Develop in-depth knowledge of Datadog’s licensing and pricing models to provide deal structuring and quoting support to our global sales teams Be a creative problem solver who finds a way to meet customers’ needs while adhering to Datadog’s selling policies Solve customer satisfaction issues following execution of the deal Actively negotiate deals directly with the customer as needed Work cross functionally across various stakeholder groups including legal, contracts, sales operations, order management, revenue, finance and product management Function as point of contact and subject matter expert for Sales on deal pricing matters Drive adherence to internal controls, protocols and business rules Who You Are: Experienced in 4+ years of Deal Desk experience Confident in deal structuring/quoting complex SaaS transactions for a fast-growing global company Knowledgeable of revenue recognition principles Comfortable representing the company to customers in negotiations and resolving customer satisfaction issues Strong in your attention to detail and communication skills Able to work independently and multi-task in fast paced, high pressure environment Data-driven with strong quantitative skills Analytical with the ability to approach a problem from multiple perspectives Bonus Points: Experience with Salesforce and CPQ Advance level with MS Excel or similar. Datadog values people from all walks of l

Citi's Markets Quantitative Analysis (MQA) group is seeking a highly skilled VP Quantitative Analyst to join its Equities team. This role is central to the research, design, implementation, and maintenance of cutting-edge Equities Execution Algorithms for Citi's clients and internal trading desks, with a specific focus on North America and LATAM markets. This position offers a unique opportunity to apply strong quantitative, technical, and soft skills to foster innovation within a collaborative team culture, directly impacting trading businesses, control functions, and the global client base. Key Responsibilities Algorithmic Development & Enhancement: Design and develop new algorithms and strategies for the next generation equity trading platform initiative at Citi. Research, design, and implement improvements for existing algorithmic trading strategies (e.g., VWAP, liquidity seeking). Develop and enhance quantitative models, including optimal schedule, market impact models, and short-term predictive signals (e.g., fair value). Implement algorithm enhancements and customizations with production-quality code, applying best practices for modular, reusable, and robust trading components. Data Analysis & Modeling: Perform in-depth analysis of large datasets comprising market data, orders, executions, and derived analytics. Apply statistical modeling and machine learning techniques for data analysis and signal generation. Conduct flow analysis and performance tuning for various client flows. Provide data and analysis to support initial model validation and ongoing performance analysis. Collaboration & Support: Collaborate closely with traders, risk managers, product, sales, and technology teams to integrate quantita

About the Team The Intelligence and Investigations team seeks to rapidly identify and mitigate abuse and strategic risks to ensure a safe online ecosystem. We are dedicated to identifying emerging abuse trends, analyzing risks, and working with our internal and external partners to implement effective mitigation strategies to protect against misuse. Our efforts contribute to OpenAI's overarching goal of developing AI that benefits humanity. The Strategic Intelligence & Analysis (SIA) team provides safety intelligence for OpenAI’s products by monitoring, analyzing, and forecasting real-world abuse, geopolitical risks, and strategic threats. Our work informs safety mitigations, product decisions, and partnerships, ensuring OpenAI’s tools are deployed securely and responsibly across critical sectors. About the Role As a Quantitative Intelligence Analyst , you will focus on discovering novel and emerging risks in complex human–AI systems before they are well-defined, measurable, or widely understood. You will use deep subject matter expertise and quantitative tooling to surface weak, early, and unconventional risk signals. You will build analytic models that explain how harms could emerge and translate ambiguous patterns into structured, data-driven insight. Your work will help identify potential gaps in policy or coverage and operationalize previously unmeasured problems into signals that can support detection, mitigation, and planning downstream. You will develop analytical frameworks that map how new risks form, evolve, and propagate as products change, policies shift, and external events unfold. Your analyses will directly inform strategic risk prioritization and planning across the company, with regular visibility through strategic risk products. This role is based in office (hybrid, 3 days/week). Relocation support is available In this role, you will: Discover and define new quantitative risk signals where no established metrics exist, using subject matter exp

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 ,

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: Airbnb, a leader in travel and hospitality, is on a mission to create a world where anyone can belong anywhere. Long-Term Stay & Luxe is being built with 0-to-1 intensity inside a marketplace that already moves at massive scale, and this team needs people who can operate like founders while still respecting the rigor of a mature, two-sided marketplace. The Difference You Will Make: Airbnb is seeking a Staff, Advanced Analytics to be the analytics owner and strategic partner for Long-Term Stay & Luxe — setting the agenda for what gets measured and tested, building the quantitative models that underpin how the business grows, and operating as a peer to product and business leadership. A Typical Day: Own the end-to-end analytics strategy and roadmap for Long-Term Stay & Luxe — decide what to measure, what to test, and where the biggest leverage is. Prioritization decisions should exist because of your recommendations. Build and evolve the quantitative models that run the business: supply-demand balance, marketplace liquidity, pricing and take-rate models, and LTV/forecasting — going beyond dashboards to build the underlying data models and pipelines. Design and analyze experiments across pricing, search and ranking, host onboarding, and guest conversion. Develop causal-inference approaches (holdouts, proxy metrics, quasi-experimental methods) for the many cases where a clean randomized trial isn't possible given lower volumes or longer booking cycles. Act as a proactive strategic partner to product, GM, and cross-functional leaders — surface insights and recomme

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the role: Replit is the fastest way to turn ideas into software. With our powerful AI-powered Agent and Assistant, anyone can create and launch apps from natural language in just one click. Build and deploy full-stack applications directly from your browser—no setup required. Never written a line of code in your life? No problem. Replit makes software creation accessible, collaborative, and lightning-fast. Join us in our mission to empower the next generation of builders. We are seeking a Strategic Finance professional to join Replit's growing team in Foster City, CA. In this critical role, you'll work in a lean team supporting high-impact strategic and operational initiatives across the business to drive data-driven decision making. You’ll partner directly with executive leadership and the Board to align financial strategies with our ambitious growth objectives. This role reports to the Head of Finance. Roles & Responsibilities: You'll contribute to critical projects across three main core areas: Internal Strategic & Operational Initiatives Cross-Functional Partnership: Partner with Sales, Marketing, Support, Product, and Engineering teams to build financial models and analyses that drive organizational decision-making New product launches: Build and present financial models, business cases, and investment analyses for new product launches GTM Finance: Partner with go-to-market leadership to drive growth through sales capacity planning, funnel and pipeline analytics, pricing strategy and resource allocation Pricing & Packaging: Analyze pricing and packaging strategies using quantitative and qualitative frameworks to recommend optimal approaches Unit Economics: Recommend strategies that balance growth

The Opportunity The world of design is changing rapidly, and the Pro Design team is leading that transformation. We are the Adobe organization behind Illustrator, InDesign, and emerging experiences that connect creativity, collaboration, and AI. Our teams are reimagining what professional design looks like for the next decade - building intelligent, connected tools that empower creators and teams to move faster without sacrificing craft. We are looking for a Senior Business Data Scientist who is creative, analytical, and unafraid to question the status quo and shape the decisions that move key business metrics at scale. Join us and build Adobe’s future products! What you'll Do Map the user funnel and build the metrics, cohorts, and dashboards that Product and Growth rely on to see how users move across free, trial, and paid tiers—and pinpoint where they drop off. Dig into the hard questions (what drives activation, which behaviors predict retention and expansion) and build propensity models for conversion, upgrade, churn, and expansion that feed real-time targeting and in-product nudges. Find and size growth bets and work with Product to ship them. Set north-star, driver, and guardrail metrics with your partners, and stand up multivariate experiments across onboarding, paywalls, in-product prompts, and pricing. What you need to succeed Minimum Requirements: Bachelor's degree in a quantitative field (Statistics, Mathematics, Computer Science, Economics, Engineering, or similar) or equivalent practical experience. 5+ years of experience in data science, product analytics, or a similar quantitative role. Proficiency in SQL and Python (or R) for data manipulation, analysis, and modeling. Hands-on experience designing and analyzing A/B tests and interpre

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join We are seeking a highly skilled and experienced professional to join our team as the Payments Insights Analytics Lead. In this role, you will play a critical part in executing the strategic direction of Airbnb's Payments operations. Within this role, you will enable, facilitate, and assist in streamlining integrated data-driven decision making across the Payments Platform, Product, Operations organizations. The team is committed to operational excellence and Host and Guest experience through a culture of problem-solving, guided by data and research. We inject quantitative measurements into our user journey, product, processes and implement objective indicators of success. You will collaborate in the development and implementation of policies and procedures related to receiving and processing funds. Oversee the day to day operations in partnership with finance across collection, reconciliation and settlement (e.g., timely processing of payments motioning systems for issues). Collaboration will be a key aspect of this role, as you will work closely with cross-functional teams to drive process improvements and streamline payments data globally. Your ability to effectively communicate and build relationships with stakeholders at all levels of the organization will be essential in achieving our goals. The Difference You Will Make You are passionate about solving complex problems within the Payments domain using data, insights, AI/ML models, and experimentation; adding a new perspective to existing solutions and making business decisions based on careful and thoughtful analysis You are hig

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. We work closely with research, software, and external hardware partners to shape the next generation of AI systems, from silicon through full-scale deployments. Our team focuses on understanding and optimizing performance across the full system stack—ensuring that architectural decisions are grounded in rigorous, quantitative analysis of real-world workloads. About the Role We are seeking a Performance Modeling Lead to build and lead a small, high-impact team responsible for answering forward-looking architectural questions across AI infrastructure systems. You will develop modeling frameworks and methodologies to evaluate system-level tradeoffs and guide key design decisions. Your work will directly influence reference architectures, vendor designs, and long-term infrastructure strategy. This role sits at the intersection of AI workloads, system architecture, and quantitative modeling, and requires strong technical judgment, ownership, and the ability to translate complex analysis into clear, actionable guidance. 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. Key Responsibilities Build and own a performance modeling framework/toolchain to evaluate AI systems across multiple levels of abstraction. Analyze and quantify architectural tradeoffs across compute, memory, networking, storage, and system topology. Develop performance models to guide decisions on: scale-up vs. scale-out architectures interconnect and network design memory hierarchy and system balance. Translate modeling outputs into clear recommendations for internal teams and external hardware vendors. Influence reference designs and vendor roadmaps through data-driven insights. Partner closely with machine learning, systems, and hardware teams to understand workload characte

About the Role OpenAI’s Industrial Compute organization is responsible for ensuring our compute infrastructure scales efficiently to support millions of users and increasingly sophisticated AI models. We’re looking for a Data Scientist to partner closely with Capacity Systems Engineering, Infrastructure, Product, and Research to optimize inference capacity across our global GPU fleet. This role combines statistical modeling, large-scale data analysis, forecasting, and systems thinking to drive critical decisions around infrastructure investments, performance-efficiency trade-offs, and customer experience. You’ll transform complex operational data into actionable insights that directly influence how OpenAI allocates and scales one of the world’s largest AI compute environments. Key Responsibilities Build statistical and machine learning models to profile and improve GPU utilization, latency, throughput, and overall fleet efficiency. Develop forecasting models for inference demand across products, regions, and model families. Analyze production workloads to identify latency bottlenecks and capacity constraints, highlighting optimization opportunities. Partner with Capacity Systems Engineering to inform infrastructure planning and long-term GPU investment strategies. Design experiments and simulations to evaluate scheduling policies, serving strategies, and infrastructure tradeoffs. Build dashboards and operational metrics that enable leadership to make data-driven capacity decisions. Collaborate with Product, Research, Finance, and Infrastructure teams to align compute planning with business growth and model roadmaps. Communicate technical findings clearly to both engineering teams and executive leadership. Qualifications MS or PhD in Statistics, Computer Science, Operations Research, Applied Mathematics, Economics, or related quantitative discipline (or equivalent industry experience). 5+ years of experience working in the infrastructure data science space. Strong ex

About the team The Intelligence and Investigations team seeks to rapidly identify and mitigate abuse and strategic risks to ensure a safe online ecosystem in close collaboration with our internal and external partners. Our efforts contribute to OpenAI's overarching goal of developing AI that benefits humanity. This role focuses specifically on AI Safety: understanding and mitigating risks created or amplified by increasingly capable AI systems. It is not a cybersecurity, information security, or corporate security role. The Strategic Intelligence & Analysis (SIA) team provides safety intelligence for OpenAI’s products by monitoring, analyzing, and forecasting real-world abuse, geopolitical risks, and strategic threats. Our work informs AI safety mitigations, product decisions, and partnerships, ensuring OpenAI’s tools are deployed responsibly across critical sectors. About the role We are looking for a Frontier AI Risks Lead to help us understand potential harms and misuse of AI in a time of rapid, sustained change. We seek to understand how developments in AI could intersect with misuse and abuse, accelerating existing harm areas and creating novel risks. We seek to scan available signals and use strategic foresight methodologies to enable proactive detection and mitigation of frontier AI risks. This is an AI safety role focused on frontier and systemic risks, including model misalignment, recursive self-improvement (RSI), multi-agent interaction, loss of control, runaway agents, and related emerging failure modes. In this role, you will help provide a strategic-level perspective on a range of frontier AI safety areas, producing actionable understanding of issues relevant to OpenAI’s platforms, systems, and broader mission. Utilizing mixed quantitative and qualitative methodologies, you will spot early warning signs, pull threads on potentially concerning behavior, and turn weak signals into clear, prioritized risk calls. You will focus on upstream ecosystem sc

Hyliion is committed to creating innovative solutions that enable clean, flexible and affordable electricity production. The Company’s primary focus is to develop distributed power generators that can operate on various fuel sources to future-proof against an ever-changing energy economy. Job Purpose The Senior Strategy & Supply Chain Associate is responsible for proactively assisting in the development of sourcing strategies that are aligned with business and program needs and then driving execution of those strategies while ensuring quality, delivery, and cost targets are exceeding expectations. Duties and Responsibilities Strategic Problem-Solving: Apply a structured, hypothesis-driven approach to diagnose complex supply chain challenges, identify root causes, and develop data-backed solutions. Data Analysis and Modeling: Conduct quantitative analysis using large datasets from our ERP and supply chain data. Develop and maintain analytical models to optimize key supply chain metrics such as inventory levels, lead times, and product economics. Process Optimization and Redesign: Lead high-impact projects to re-engineer core supply chain processes, leveraging best practices to drive significant improvements in efficiency, cost, and resilience. Cross-Functional Collaboration: Serve as a trusted advisor to internal stakeholders in Engineering, Finance, and Operations. Effectively communicate complex analyses and recommendations to senior leadership, fostering alignment and driving execution. Performance Management: Design, implement, and monitor key performance indicators (KPIs) and dashboards to track supply chain health and project performance. Provide regular, insightful reports to management on progress against strategic objectives. Supplier and Sourcing Strategy: Collaborate with the Procurement team to analyze supplier capabilities, assess market dynamics, and develop commodity and category strategies that align with bot

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 Multifamily Capital Markets is seeking an exceptionally curious, analytical, and driven professional to help identify, prioritize, and deliver the initiatives that can most improve the business. This is a rare opportunity to develop a broad view across the Multifamily Capital Markets organization, including loan pricing, pipeline risk management, portfolio management, securitization, credit-risk transfer, operations, and technology. You will work directly with a Capital Markets leader who brings deep Multifamily expertise, extensive Wall Street markets and product experience, and a track record of developing innovative solutions to complex financial problems. Together, you will examine how the business operates, identify its highest-impact opportunities, challenge existing assumptions, and develop solutions from first principles. This is a hands-on role combining original problem-solving, quantitative analysis, and end-to-end initiative delivery. You will research unfamiliar topics; analyze financial, market, and operational data; build analytical models and lightweight Python prototypes; test hypotheses; frame business questions; and develop fact-based recommendations. You will write the memos and presentations that move decisions forward, document conclusions and requirements, coordinate contributors, maintain project plans and follow-ups, and drive multiple initiatives through organizational and technical roadblocks from initial idea through implementation. This role is designed for someone who enjoys learning unfamiliar topics, solving difficult problems, and taking ownership of outco