Markets Quantitative Analyst Jobs

Markets Quantitative Analyst - Capital Analytics — New York New York United States. Apply via Workday.

Markets Quantitative Analyst - Capital Analytics, AVP — London United Kingdom. Apply via Workday.

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

We are seeking an experienced Quantitative Developer to join our Markets Quantitative Analytics team, partnering closely with Quantitative Analysts, Traders, and Technology professionals to build the next generation of pricing, risk, and analytics platforms. This is a hands-on technical role for a highly skilled software engineer with a passion for quantitative finance. You will be responsible for designing and delivering high-performance, scalable solutions that support front office trading businesses across asset classes. The role offers the opportunity to work on complex quantitative challenges, modern engineering practices, and large-scale distributed systems while helping shape the strategic direction of Citi's quantitative technology platform. Successful candidates will combine strong software engineering expertise with an understanding of quantitative methodologies and financial markets, translating sophisticated mathematical models into robust, production-grade solutions. Key Responsibilities Design, develop, and maintain high-performance pricing, risk, and analytics libraries used across Global Markets. Partner with Quantitative Analysts to transform research models and prototypes into scalable, production-quality software. Build and optimize quantitative applications using modern C++ and Python, applying strong software architecture and engineering principles. Own the full software development lifecycle, including requirements gathering, design, implementation, testing, deployment, and ongoing support. Drive engineering excellence through CI/CD adoption, automated testing, code reviews, and software quality best practices. Develop and maintain market data platforms and data pipelines supporting analytics, pricing, and risk workflows. Work with infrastructure teams to leverage distributed computing, cloud technologies, and scalable arc

Capital Markets Analyst - Quantitative — McLean, VA. Apply via Workday.

Description: Graviton is a privately funded quantitative trading firm striving for excellence in financial markets' research. We are seeking a Quant Analyst - Risk for our team in Gurugram. Graviton trades across a multitude of asset classes and trading venues using a gamut of concepts and techniques ranging from time series analysis, filtering, classification, stochastic models, pattern recognition to statistical inference analysing terabytes of data to come up with ideas to identify pricing anomalies in financial markets. As a Quant Analyst - Risk you will be responsible Work as a team with senior traders to operate and implement/improve our automated trading strategies. Analysing production trades and developing ideas to improve our trading strategies. Implement monitoring tools which highlight potential issues in the production strategies. Write comprehensive and scalable scripts in both C++ and python analysing production strategies for risk attribution, performance break-ups along various buckets and so on. Build ‘cool’ scalable post-trade systems analysing multitude of statistics across all production strategies. Implementing tools for analysing Market Data centrally across various exchanges. Managing deployments and release cycle, with working along with a senior trader. Requirements : Possess a degree in a highly analytical field, such as Engineering, Mathematics, or Computer Science from top-ranked universities 3+ years of experience in Python, Shell/Bash scripting. Basic knowledge of Linux and shell command-line tools Basic programming and scripting (Python/Shell) skills Strong problem-solving, and analytical skills Excellent communication skills Have a strong work ethics Mentorship experience in guiding junior developers. Benefits: Our open and collaborative work culture gives you the freedom to innovate and experiment. Our cubicle free offices, non-hierarchical work culture and insistence to hire the very best creates a melting pot for great idea

About BlockTech BlockTech is a fast-paced algorithmic trading firm at the frontier of global cryptocurrency derivatives and spot markets. We trade 24/7 across some of the most data-rich, fast-moving venues in finance, and we use that data to build smarter models, sharper signals, and more adaptive systems. Crypto is one of the few markets where a researcher can still meaningfully move the edge. The data is abundant, the microstructure is novel, and the feedback loop between a research idea and live PnL couldn’t be shorter. We’re growing fast, and we’re looking for a Quantitative Researcher with a strong machine learning toolkit to help us push that edge further. The role As a Quantitative Researcher on our trading floor, you’ll own ideas end-to-end from hypothesis and dataset construction through feature engineering, model training and backtesting, all the way to live deployment, monitoring, and iterative improvement. You’ll sit shoulder-to-shoulder with Quantitative Traders and Quantitative Analysts, and your work will directly drive how we price and trade. What you’ll work on Collaborating closely with traders to translate research insights into systematic trading strategies Designing, developing and deploying models for price prediction, signal generation, execution, and anomaly detection across crypto derivatives and spot markets using state-of-the-art AI and ML techniques. Building robust trading, backtesting and research infrastructure alongside our engineers, so promising ideas can move into production quickly and safely Owning models in production: monitoring live performance, diagnosing decay, and iterating on what you ship What we’re looking for A strong academic background in a quantitative discipline (Mathematics, Physics, Statistics, Computer Science, Econometrics, ML/AI, or similar), typically a PhD or an MSc with strong research experience Fluency in Python and the modern ML stack (PyTorch and/or TensorFlow, scikit-learn, NumPy, pandas) A deep, intuit

About BlockTech BlockTech is a fast-paced algorithmic trading firm at the frontier of global cryptocurrency derivatives and spot markets. We trade 24/7 across some of the most data-rich, fast-moving venues in finance, and we use that data to build smarter models, sharper signals, and more adaptive systems. Crypto is one of the few markets where a researcher can still meaningfully move the edge. The data is abundant, the microstructure is novel, and the feedback loop between a research idea and live PnL couldn’t be shorter. We’re growing fast, and we’re looking for a Quantitative Researcher with a strong machine learning toolkit to help us push that edge further. The role As a Quantitative Researcher on our trading floor, you’ll own ideas end-to-end from hypothesis and dataset construction through feature engineering, model training and backtesting, all the way to live deployment, monitoring, and iterative improvement. You’ll sit shoulder-to-shoulder with Quantitative Traders and Quantitative Analysts, and your work will directly drive how we price and trade. You will: Collaborate closely with traders to translate research insights into systematic trading strategies Design, develop and deploy models for price prediction, signal generation, execution, and anomaly detection across crypto derivatives and spot markets using state-of-the-art AI and ML techniques. Build robust trading, backtesting and research infrastructure alongside our engineers, so promising ideas can move into production quickly and safely Own models in production: monitoring live performance, diagnosing decay, and iterating on what you ship What we're looking for A strong academic background in a quantitative discipline (Mathematics, Physics, Statistics, Computer Science, Econometrics, ML/AI, or similar), typically a PhD or an MSc with strong research experience Fluency in Python and the modern ML stack (PyTorch and/or TensorFlow, scikit-learn, NumPy, pandas) A deep, intuitive grasp of overfitting, g

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 Yondr Yondr is a disruptor. We challenge convention and simplify complexity. A global developer, owner operator and service provider of data centers, we deliver complex data center capacity needs for the world’s largest tech companies. Our exponential growth sees us looking for extraordinary people to help accelerate us towards our vision: a tomorrow without constraints. But we can’t do this without you. About the Role With continued growth across our business, we are actively seeking to have a new member join our team. This is an exciting role to join an existing group of skilled development and investment professionals, enhancing the team capabilities and becoming an integral part of a rapidly growing business. We are searching for someone who has excellent quantitative and analytical skills, is comfortable building financial models and has experience with communicating with internal and external stakeholders. You will be a highly valued and trusted member of our ambitious and hardworking team, in a business that continues to scale to new heights. Main Responsibilities / Take responsibility for development and management of financial models and valuation analysis in support of potential transactions and investment opportunities / Support in all aspects of financing processes included due diligence, project management, data room management, financial analysis, legal negotiations and preparation of materials / Work closely with the Development and Finance teams to perform detailed financial analysis on new developments as well as existing portfolio assets / Production of presentation material for senior management, board members, investors, lenders and joint venture partners / Assist with commercial negotiation of legal contracts for transactions / Research and analysis of market trends and sector / asset valuations / Support in business strategy and individual project delivery /

Graviton Research Capital is one of the largest quantitative trading firms in APAC, with a strong footprint across 40+ global exchanges and a rapidly growing presence across multiple geographies. We are a bootstrapped firm with a long-term vision, focused on building high-performance teams that operate at scale in some of the world’s most competitive markets. Since our inception, we have built a team of exceptional researchers, portfolio managers, and technologists. We are seeking an Operations Analyst ( middle office ) for our team in Singapore. What You Will Do: Oversee daily trade bookings, position and P&L reconciliations, settlement challenges, and corporate action events Ensure accurate and timely delivery of reports on trades, positions, cash holdings, costs, and P&L attribution Manage all operational aspects throughout the trade lifecycle, from initiation to settlement Liase with counterparties, custodians, and prime brokers to on-board new businesses and address daily issues Identify and drive process improvement initiatives, focusing on increasing operational efficiency and scalability. Design and implement automated solutions that streamline workflows using best practices in data management and automation. What You Need to Succeed: 2 to 5 years of Middle Office/Operations experience, preferably from a buy-side environment (Hedge funds, Prop Trading) or Prime brokerage Solid product knowledge in listed equities (a must), ETFs, derivatives, and FX Familiarity with Asian securities markets and their respective regulations is preferred Proficient in Excel, with practical experience in VBA, SQL, and Python Demonstrated experience in process improvements and designing automated solutions, ideally within a trading environment Excellent problem-solving skills with a proactive approach to identifying and addressing areas for improvement Why Join Graviton? Work in a high-performance, data-driven trading environmen

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto remains one of the few markets where a researcher can still meaningfully move the edge: abundant data, novel microstructure, and the shortest possible loop between a research idea and live PnL. We're looking for an experienced Quantitative Researcher to take ownership of that edge and push it further. The role This is a senior, hands-on research seat on our trading floor. You'll own a research agenda end-to-end from hypothesis, dataset construction, feature engineering, model training, backtesting, live deployment, monitoring, and iteration. You'll be trusted to set its direction. You'll work shoulder-to-shoulder with fellow researchers, traders and analysts, shape how we price and trade, and help raise the bar for research across the floor, including mentoring less experienced researchers and influencing the tools and standards the team relies on. You will: Own price-prediction, signal, execution, and anomaly-detection models across crypto derivatives and spot markets from idea to live PnL using state-of-the-art ML Shape our research, backtesting, and trading infrastructure together with engineers, so good ideas reach production quickly and safely Own models in production: monitor live performance, diagnose decay, and iterate on what you ship Set research direction alongside traders, deciding which trades are worth making and why Raise the research bar by mentoring colleagues, reviewing work, and setting standards for rigour What we're looking for 4+ years of hands-on quantitative research and/or applied ML experience, with a track record of models you've taken into production trading live A strong academic foundation in a quantitative discipline (mathematics, physics, statistics, computer science, ML/AI, or similar) Fluency in Python and the modern

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto remains one of the few markets where a researcher can still meaningfully move the edge: abundant data, novel microstructure, and the shortest possible loop between a research idea and live PnL. We're looking for an experienced Quantitative Researcher to take ownership of that edge and push it further. The role This is a senior, hands-on research seat on our trading floor. You'll own a research agenda end-to-end from hypothesis, dataset construction, feature engineering, model training, backtesting, live deployment, monitoring, and iteration. You'll be trusted to set its direction. You'll work shoulder-to-shoulder with fellow researchers, traders and analysts, shape how we price and trade, and help raise the bar for research across the floor, including mentoring less experienced researchers and influencing the tools and standards the team relies on. What you'll do Own price-prediction, signal, execution, and anomaly-detection models across crypto derivatives and spot markets from idea to live PnL using state-of-the-art ML Shape our research, backtesting, and trading infrastructure together with engineers, so good ideas reach production quickly and safely Own models in production: monitor live performance, diagnose decay, and iterate on what you ship Set research direction alongside traders, deciding which trades are worth making and why Raise the research bar by mentoring colleagues, reviewing work, and setting standards for rigour What we're looking for 4+ years of hands-on quantitative research and/or applied ML experience, with a track record of models you've taken into production trading live A strong academic foundation in a quantitative discipline (mathematics, physics, statistics, computer science, ML/AI, or similar) Fluency in Python and the m

JLL empowers you to shape a brighter way . Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology for our clients. We are committed to hiring the best, most talented people and empowering them to thrive, grow meaningful careers and to find a place where they belong. Whether you’ve got deep experience in commercial real estate, skilled trades or technology, or you’re looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward. Research Analyst – JLL What this job involves: The Research Analyst will join JLL's San Francisco Research team to deliver market intelligence that sets JLL apart. You will analyze San Francisco's industrial, office, and flex markets alongside the economic drivers that shape them. This role combines direct client engagement with hands-on data analysis, positioning you at the intersection of urban economics and commercial real estate. You will grow from foundational market research into automated workflows, quantitative modeling, and independent analysis—building both analytical rigor and technical capability. If you're curious about what drives markets and ready to become data fluent while mastering local real estate dynamics, this role offers a clear path forward. What your day-to-day will look like: Develop expertise on San Francisco's economy, industry composition, demographics, and commercial real estate market to identify trends and emerging opportunities Maintain comprehensive market coverage by tracking significant leasing activity, tenant movements, development projects, sales transactions, and ownership changes Meet regularly with clients and internal teams to present market insights, conditions, and forecasts Produce quarterly reports on San Francisco market

Given heightened expectations from regulators and a goal to build a strong and consistent global control environment, Citi continues to enhance its business governance framework and has created the Enterprise Data group. Enterprise Data is a critical component of Citi’s first line of defense for wholesale and counterparty credit risk management and works with Independent Risk teams to ensure best-in-class risk and controls, as well as client responsiveness. Key responsibilities of the group include credit analysis, documentation, risk identification, exposure monitoring and stress testing. Enterprise Data coordinates with credit management groups across institutional client businesses to ensure full alignment on business and regulatory goals, as well as consistency and best practices. The Counterparty Credit Risk (CCR) project execution team within Enterprise Data is responsible for building tools to: Provide in-depth quantitative or qualitative analysis to solve business problems and develop new, innovative solutions Build tools to help measure, monitor and control counterparty risk for institutional clients and Portfolios and businesses, with a focus on counter-party and collateral risk to ensure the risks are being properly measured and controlled in accordance with the Firm’s risk policies. Responsibilities: As a Product Developer working in CCR project team, individual will be expected to Lead strategic BAU and Regulatory projects primarily impacting Counterparty Credit Risk exposure measures for traded product markets business Develop and enhance tools for the measurement, monitoring and reporting of counterparty exposure including Stress testing - Net Stressed Exposure (NSE), Potential Future Exposure (PFE), Settlement Risk, Intraday risk and participate in project management of strategic risk infrastructure development.</