Quantitative Trader in United States

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

Chicago Trading Company (CTC) is a premier proprietary trading firm specializing in options market making. Our collaborative culture fuels innovation in quantitative research, systematic trading strategies, and cutting-edge trading technology. For over three decades CTC has provided critical liquidity across derivatives exchanges worldwide - making them fairer, more transparent, and more efficient. We strive to be the most innovative firm in the industry today, tomorrow, and long into the future while upholding ethical excellence. We believe that CTC makes a positive impact on the markets, the lives of our employees, and all the communities to which we belong. Started in 1995 by a team of forward-thinking Traders, we are proud to call ourselves an industry leader that keeps making markets and each other better. The Role As a Quant Trading (QT) Intern, you will be challenged to learn and adapt in an exciting team environment and will play a substantial role in our day-to-day trading and quant-related activities. Your impact is immediate and meaningful. You will become a member of a team for the summer and play a vital role completing project work and/or identifying trading opportunities and communicating with software engineers, quants, traders, and risk managers throughout the trading day. As part of the Summer Associate cohort, you will learn and socialize alongside other QT Interns and Software Engineering (SE) Interns. What to Expect The 8-week internship program gives you insight into our culture and an inward look into what our business is all about. You will participate in three classroom learning experiences including: a week-long Basics of Options class, a multi-week class on the fundamentals of market making (Mock Trading), and a multi-week class that introduces elements of our quant framework (Quant Curriculum). You will also attend planned social activities and talks from various business leaders to propel your professional growth, and

Chicago Trading Company (CTC) is a premier proprietary trading firm specializing in options market making. Our collaborative culture fuels innovation in quantitative research, systematic trading strategies, and cutting-edge trading technology. For over three decades CTC has provided critical liquidity across derivatives exchanges worldwide - making them fairer, more transparent, and more efficient. We strive to be the most innovative firm in the industry today, tomorrow, and long into the future while upholding ethical excellence. We believe that CTC makes a positive impact on the markets, the lives of our employees, and all the communities to which we belong. Started in 1995 by a team of forward-thinking Traders, we are proud to call ourselves an industry leader that keeps making markets and each other better. The Role As a Software Engineering (SE) Intern, you will be challenged to learn and adapt in a dynamic, forward-thinking, and fast-paced environment and will experience life as an engineer on one of our technology teams. Your impact is immediate and meaningful. You will work alongside software engineers designing, solving and testing complex coding problems that will deliver solutions to our trading tools and risk applications. You will build the tools traders and quants rely on to price, trade, and manage risk in real time - and because our release cycles are measured in days, you will watch your code reach production and affect the desk almost immediately. This work draws on a solid foundation in computer science, software development practice, and strong communication and teamwork. You will get exposure to the design and implementation of these systems, which will allow you to build upon your technical skills. As part of the Summer Associate cohort, you will learn and socialize alongside other SE Interns and Quant Trading (QT) Interns. There are a variety of languages you could get practical experience working with including (but

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 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

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

Are you ready to be part of an ambitious team driving digital transformation at NVIDIA? As a Sr. Staff Business Systems Analyst, you will play a pivotal role in crafting intuitive, high-impact experiences that support our core business functions. This outstanding opportunity offers the chance to collaborate with global partners and influence decisions that determine our competitive edge! What you’ll be doing: Design and scale AI-powered workflows, agentic experiences, and internal products that simplify work, surface relevant context, and enable employees to complete tasks more effectively across enterprise tools. Drive internal go-to-market and adoption strategies for digital and AI capabilities, including persona-based value propositions, enablement, communications, feedback loops, and outcome measurement. Apply a product mindset to develop intuitive, simple, and high-impact experiences, starting with the user problem and connecting solutions to meaningful business outcomes. Collaborate with global partners, architects, engineers, and business leaders to define product vision, prioritize capabilities, and develop world-class systems that support NVIDIA’s core business functions. Use data, user feedback, and qualitative insights to identify opportunities and make informed decisions, leveraging strong storytelling skills to build alignment and influence priorities. Build trusted relationships with collaborators at all levels; facilitate productive discussions, navigate ambiguity, and negotiate trade-offs across user needs, technical constraints, timelines, and business value. Champion employee experience and user-centric development by continuously gathering feedback and measuring adoption, usability, satisfaction, and business impact to evolve solutions after launch. What we need to see : Bachelor’

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

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. We are accepting applications for this position until 10/16/2026 Position Overview: At Freddie Mac, you will have meaningful work to help build a better housing finance system and support homeownership and rental housing opportunities across the nation. Our internship and graduate programs provide opportunities to tackle complex challenges, contribute to strategic initiatives, and build valuable relationships with industry professionals. As a Quantitative Risk Management Intern within Enterprise Risk Management (ERM), you will apply advanced analytical, technical, and quantitative skills to support risk management activities at one of the nation's largest financial institutions. You will gain hands-on experience working on real-world projects, collaborating across teams, and leveraging emerging technologies – including artificial intelligence and automation—to enhance risk management practices and business outcomes. Our Impact: Enterprise Risk Management (ERM) helps build and maintain a strong, effective, and efficient risk management framework across Freddie Mac. We provide independent oversight and assessment of financial and non-financial risks while promoting a culture of accountability, innovation, and sound risk management. Our quantitative teams leverage advanced analytics, data science, modeling, automation, and emerging technologies to support enterprise-wide decision-making and risk oversight. As AI and automation continue to transform the financial services industry, our teams p

What you’ll do Partner with medical image reconstruction scientists / engineers to build ML components that improve reconstruction quality, speed, robustness, or quantitative accuracy. Define training/evaluation pipelines, datasets, and metrics that map to user needs and design requirements. Productionize models: inference performance, reproducibility, monitoring for drift/regressions, and safe fallbacks. Collaborate on hybrid algorithms, incorporating physics and learned priors, denoisers, learned regularizers, and quality estimation. Help build tooling for rapid experimentation as well as rigorous verification of algorithm changes. What we’re looking for Strong applied ML experience plus comfort with signal processing / imaging or adjacent domains. Ability to move fluidly between research prototypes and production-quality systems. Strong evaluation discipline: metrics, ablations, data leakage avoidance, and reproducibility. A demonstrated track record of applying ML to physics-based or inverse problems (i.e., shipped projects, a portfolio, or publications.) Useful experience ML for imaging/inverse problems (or adjacent) with strong evaluation discipline and comfort with GPU performance constraints. Pragmatic production mindset: reproducible training/inference, regression testing, and safe deployment in high-stakes contexts. A background in computational physics or scientific computing. Leverage ML-based methods such as PiNNs and Neural Operators to solve partial differential equations arising in ultrasound simulation and imaging. Experience in Agentic-SciML is a plus. Hands-on experience with data curation for ML: building datasets from messy, real-world sources, defining ground truth, and managing labeling or simulation pipelines. Background in data assimilation: combining observations with physics-based models (Kalman filtering, variational methods, ensemble approaches, or learned variants).

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Pinterest is looking for a Sr. Staff Quantitative Product Researcher to lead the development and evolution of user-centered measurement across our consumer experience. As the volume of measurement asks grows, we need a seasoned researcher who can partner with Data Science and Engineering as an equal — not just contributing to metrics work, but guiding it end-to-end and shaping the direction of how we measure the Pinner experience. In this role, you'll own the full arc of measurement work: identifying what we should be measuring, designing surveys that capture the constructs that matter, validating that our metrics are reliable and sensitive, guiding experimentation plans to prove they can move, and partnering with DS and Eng to build behavioral proxies or predictive models where they're needed. You'll also extend this work into how we evaluate a

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. This internship will take place from January 25 - April 16 and you will need to be able to work out of our SF office during this time. What You'll Achieve: Conduct data analyses to gain insights about Notion and use these insights to uncover opportunities for improvements in our product and business. Communicate these insights with actionable recommendations to cross-functional teams (insights are useful, impact is even better!). Work with cross-functional partners across the product and business to learn about their functions and use data to advance their respective areas. Create metrics and build dashboards to monitor the growth and health of Notion. Communicate insights and recommendations effectively to leadership and have an impact on strategic decision-making. Qualifications: Pursuing a bachelor's or master's in a quantitative field such as Economics, Statistics, Applied Math, Engineering, Computer Science, or Natural Sciences. Must graduate before December 2027. This internship will take place from January 25 - April 16 and you will need to be able to work out of our SF office during this time. Previous research or internship

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: Airbnb, a leader in travel and hospitality, is on a mission to create a world where anyone can belong anywhere. We offer unique accommodations and experiences, crafted and curated by locals. As we expand into new marketplaces for in-person experiences and services, we are on the lookout for driven and innovative individuals to help shape our growth trajectory. The Difference You Will Make: Airbnb is seeking a Staff, Advanced Analytics, to support our Guest App team. This individual will act as a senior thought partner, supporting strategic business and product initiatives through detailed data analysis, experimentation, statistical modeling, and the development of reporting tools and metrics. The individual will be instrumental in driving product decisions for the Guest App, especially for strategically important Promotional Merchandising initiatives, to optimize for the company's objectives and ensure optimal experiences for guests. A Typical Day: Be the Advanced Analytics owner and expert on domain datasets. Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches. Apply technical expertise with quantitative analysis, experimentation, data mining, forecasting and the presentation of data to identify trends and patterns that can inform decision-making. Collaborate closely with Product, Engineering, Finance, Marketing, Operations, Data Science, Advanced Analytics, Data and Analytical Engineering, and other cross-functional teams to provide actionable insights. Design, execute, and analyze experime

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. At Freddie Mac, you will do important work to build a better housing finance system and you’ll be part of a team helping to make homeownership and rental housing more accessible and affordable across the nation. We are accepting applications for this position until 10/16/2026 Position Overview: The Single-Family division within Freddie Mac is seeking curious, motivated college students for a summer internship. Interns will gain hands-on experience supporting data analytics, reporting, business processes, and risk management activities while building skills through mentorship, training, and collaboration. This opportunity is ideal for college juniors interested in data analytics, statistical analysis, quantitative problem solving, and emerging technologies, including AI-enabled tools. Our Impact: Single-Family uses data analysis, reporting, and risk management to support business decisions and deliver solutions for customers. We optimize, visualize, and govern data across the data lifecycle while modernizing the Single-Family data ecosystem. We leverage statistical analysis, quantitative modeling, structured rules, and emerging technologies to improve operational effectiveness. Your Impact: Assist product owners, team members, and business partners with gathering requirements, documenting user stories, and clarifying project scope. Support day-to-day operations and projects through data analysis, impact analysis, user acceptance testing, reporting, and other business or technical support activities. Coll