Quantitative Insurance Solutions Analyst Jobs

About BlockTech BlockTech is a fast-paced algorithmic market maker at the frontier of global cryptocurrency derivatives and spot markets, expanding into new markets. We employ algorithms to trade our own capital, 24/7, across some of the most data-rich venues in finance. 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 could not be shorter. For the Summer of 2027, we're looking for a Quantitative Research Intern to join our Delta One team in Singapore. The role This is a 12-week summer internship at our Singapore office, giving you a unique opportunity to work on an end-to-end project with a real and direct business impact. You'll work in a small team and get the chance to understand how a trading firm actually works from the inside. Delta One is where we trade linear products: (perpetual) futures and spot. These are fast-moving, data-rich markets and a good place to see a research idea meet reality quickly. You will: Participate in a customized training program that will give you an understanding of financial markets in general, the company, and the project. Own a research project from design to deployment, guided by experienced Quantitative Researchers. Work with linear products and the data around them Understand how technology and research enable our trading, market data, and infrastructure systems. Collaborate with fellow quantitative researchers and software engineers to bring your project to success. Learn from the best, using technology built for speed and precision. What we're looking for Currently in your (pen)ultimate year studying a quantitative field at a top university in Singapore Available full-time in Singapore for a duration of 12 weeks over the summer of 2027, starting on the 10th of May Working knowledge of Python Comfort with probability, statistics, and working with messy real-world data A critic

Quant/Developer Analyst for a Discretionary Macro Investment Team focused on Structured Products A Career with Point72’s Macro Team Point72’s Global Macro business is a scaled, global investment platform with more than two decades of experience trading across rates, FX, credit, volatility, and emerging markets. Operating across 10 offices worldwide, we have doubled our capital allocation and grown our number of teams fivefold since 2020. We combine deep asset-class expertise with a highly collaborative culture across macro, fundamental equities, and systematic strategies to drive differentiated investment performance and support long-term career growth for our talent. What you’ll do Help architect and maintain the infrastructure for Structured Products investing. Leverage internal and external partners to help with data infrastructure builds. Integrate alternative and traditional data sets to help streamline our analytic processes. Use Artificial Intelligence (AI) to enhance and optimize processes. Work with risk parameters based on High Yield Equivalent and quantitative processes within market-standard analytics platforms such as Bloomberg. Manage and assist in special projects within the CLO market. What’s required 3+ years at a sell-side firm in a trading or quantitative research role, or as a quant at a buy-side credit or mortgage-focused fund. Undergraduate degree or higher in computer science, economics, engineering, mathematics, physics, or statistics. Advanced knowledge of a programming language such as Python, C++, or SQL. Advanced skills in Excel and cashflow modeling. Extensive experience with third-party structured credit cashflow engines (e.g., INTEX) and API. Commitment to the highest ethical standards. We take care of our people We invest in our people, their careers, their health, and their well-being. When you work here, we provide: Fully-paid health care benefits Generous parental and family leave policies Volunteer opportunities Support for employ

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 is one of the few markets where the gap between a good model and live PnL comes down to how fast and how reliably you can ship it. Abundant data, novel microstructure, and a short path to production mean the quality of our infrastructure directly moves the edge. We're looking for a Quantitative Developer to build that infrastructure and get our models into production. The role This is a hands-on engineering seat on our trading floor. You'll own the infrastructure that turns research models into production trading systems, working primarily in Python and Rust, the language our models and systems are written in. You'll build the frameworks and tooling that let quants ship their code to production and keep those systems running once they're live. You'll work shoulder-to-shoulder with researchers, traders, and fellow engineers, building the tooling, pipelines, and standards that let good ideas reach production quickly and safely, and helping raise the engineering bar across the floor. You will Build and own the infrastructure that takes models from research to production - data pipelines, backtesting, deployment, and monitoring. Turn research prototypes into robust, performant, production-grade code that runs reliably in live trading Work closely with quantitative researchers and traders to get new models live quickly and safely Own the systems you ship in production: monitor performance, diagnose issues, and keep latency and reliability high Improve the tools, standards, and pipelines the team relies on, raising the engineering bar across the floor What we're looking for 2+ years of software engineering experience, with a track record of shipping production-grade systems A strong academic foundation in a STEM discipline (computer science, mathematics, p

About BlockTech As a Quantitative Trader on our Singapore trading floor, you’ll own positions and PnL end-to-end from interpreting live market flow and liquidity through tuning and intervening in our automated systems, all the way to shaping the next generation of execution logic and trading tools. You’ll sit shoulder-to-shoulder with Quantitative Researchers, Quantitative Developers, and Software Engineers, and your decisions will directly drive how we trade across venues. The role Managing and monitoring Delta1 positions across multiple venues, owning the PnL and risk that comes with them Reading live market flow, liquidity conditions, and market events, and translating that read into concrete trading and execution decisions Tuning and parameterising our automated and semi-automated systems, and knowing when to step in to manage risk or capture an opportunity Improving execution quality and market-making performance through data-driven analysis of strategy behaviour Designing and specifying the trading tools, dashboards, and analytics that the desk relies on to make decisions Collaborating closely with researchers, developers, and engineers to sharpen models, infrastructure, and execution logic, and shaping the roadmap for new trading initiatives What we’re looking for 3+ years of experience as a Quantitative Trader and/or Quantitative Researcher in a professional trading environment, with demonstrated PnL responsibility on linear (Delta1) products across multiple venues Hands-on experience operating automated and semi-automated trading systems under live conditions: monitoring, tuning, and intervening when it matters Strong analytical instincts: you can take a messy dataset of fills and quotes and turn it into a concrete execution improvement A deep, intuitive grasp of market microstructure and the ability to explain why a strategy works, not just that it does Proficiency in Python for analysis, tooling, and interaction with trading systems An ownership mindset:

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: Freddie Mac’s Investments & Capital Markets Division is seeking a Quantitative Analytics Senior to develop, implement, monitor, and execute quantitative models that support counterparty credit risk management, fixed-income derivatives valuation, and related business and risk management decisions. The candidate should be self-motivated, has a strong quantitative and computational background, and communicates effectively with technical and business stakeholders. As part of the Models & Analytics team, this role will primarily support Freddie Mac’s Counterparty Credit Risk Management and Asset-Liability Management functions, with responsibilities spanning model development, implementation, monitoring, data processes, documentation, and business user support. Our Impact: This role focuses on the design, development, implementation, and monitoring of quantitative models and analytics that support counterparty credit risk, exposure measurement, derivatives valuation, and related risk management activities. The models and analytics developed by the team provide key inputs into counterparty credit risk management, portfolio management, business reporting, and risk-informed decision-making across the division. Your Impact: • Develop, implement, and maintain quantitative models primarily for counterparty credit risk measurement, with additional coverage of interest rates, derivatives valuation, and valuation components related to mortgage products. • Implement models and analytics using programming languages and tools such as MATLAB,

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: Freddie Mac’s Investments & Capital Markets Division is currently seeking a Quantitative Analytics Senior to be responsible for the creation, development, and execution of analytic models used to value Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) of various types of financial institutions. The candidate should be self-motivated, have a strong computational background, and effective communication skills. Under the Models & Analytics team, the candidate will support models primarily utilized by Freddie Mac’s Counterparty Credit Risk Management Team. The key focus is on credit risk scorecard modeling, but the tasks may also include LGD and EAD models. The position encourages continued learning and development across other modeling areas, including market risk capital, operational loss forecast, prepayment and default, and rates and derivatives . Our Impact: Key focus of this job is the design, development, and implementation of counterparty credit risk models for a variety of financial institutions, with primary focus on Probability of Default modeling. These models support multiple corporate and divisional objectives by providing key inputs into counterparty credit risk management, both at individual counterparty and portfolio levels. Y our Impact: Design, code and maintain consistent counterparty credit risk models (PD/LGD/EAD). These models must incorporate best practices while simultaneously accounting for the

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. We’re looking for an intelligent, driven professional to join our Bank Model Risk Management (MRM) team. This team seeks to establish, maintain and oversee an effective MRM framework to identify, quantify, monitor, mitigate and report on model risk. You will have an outstanding opportunity to work cross-functionally to develop a profound understanding of models that drive critical business decisions, and add value to the Bank by mitigating risks due to ineffective model design or model misuse. What You'll Do Full-Stack Model Validation: Conduct rigorous, independent validations of sophisticated credit/fraud models—including machine learning and traditional statistical models—focusing on conceptual soundness, data integrity, and performance stability. Advanced Quantitative Monitoring: Develop automated, independent monitoring suites in Python to track KRI/KPI drift, population stability (PSI), and feature importance shifts in real-time. Remediation & Technical Advisory: Partner with 1st-line Model Developers to drive the remediation of validation findings, ensuring models and strategies are not only compliant but mathematically robust. Audit & Regulatory Liaison: Partner with Internal Audit, Internal Controls, and Compliance to facilitate the timely resolution of audit and regulatory requests. Affirm Bank: Work for the internal Bank team to support the build out of the Bank Model Risk Management function. Support the model validation requirements for Bank owned models. What We Look For 7+ years of professional experience in a highly technical capacity, such as Credit/Fraud/Financial Risk Modeling, Model Validation, or Quantitative Analytics Deep understanding of the consumer credit lifecycle and/or fraud detection. Technical familiarity with loss forecasting/fraud prediction, a

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 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 is one of the few markets where the gap between a good model and live PnL comes down to how fast and how reliably you can ship it. Abundant data, novel microstructure, and a short path to production mean the quality of our infrastructure directly moves the edge. We're looking for a Quantitative Developer to build that infrastructure and get our models into production. The role This is a hands-on engineering seat on our trading floor. You'll own the infrastructure that turns research models into production trading systems, working primarily in Python and Rust, the language our models and systems are written in. You'll build the frameworks and tooling that let quants ship their code to production and keep those systems running once they're live. You'll work shoulder-to-shoulder with researchers, traders, and fellow engineers, building the tooling, pipelines, and standards that let good ideas reach production quickly and safely, and helping raise the engineering bar across the floor. You will Build and own the infrastructure that takes models from research to production - data pipelines, backtesting, deployment, and monitoring. Turn research prototypes into robust, performant, production-grade code that runs reliably in live trading Work closely with quantitative researchers and traders to get new models live quickly and safely Own the systems you ship in production: monitor performance, diagnose issues, and keep latency and reliability high Improve the tools, standards, and pipelines the team relies on, raising the engineering bar across the floor What we're looking for 2+ years of software engineering experience, with a track record of shipping production-grade systems A strong academic foundation in a STEM discipline (computer science, mathematics, p

About BlockTech As a Quantitative Trader on our Singapore trading floor, you’ll own positions and PnL end-to-end, from interpreting live market flow and liquidity through tuning and intervening in our automated systems, all the way to shaping the next generation of execution logic and trading tools. You’ll sit shoulder-to-shoulder with Quantitative Researchers, Quantitative Developers, and Software Engineers, and your decisions will directly drive how we trade across venues. The role Managing and monitoring D1 positions across multiple venues, owning the PnL and risk that comes with them Reading live market flow, liquidity conditions, and market events, and translating that read into concrete trading and execution decisions Tuning and parameterising our automated and semi-automated systems, and knowing when to step in to manage risk or capture an opportunity Improving execution quality and market-making performance through data-driven analysis of strategy behaviour Designing and specifying the trading tools, dashboards, and analytics that the desk relies on to make decisions Collaborating closely with researchers, developers, and engineers to sharpen models, infrastructure, and execution logic, and shaping the roadmap for new trading initiatives What we’re looking for 3+ years of experience as a Quantitative Trader and/or Quantitative Researcher in a professional trading environment, with demonstrated PnL responsibility on linear (D1) products across multiple venues Hands-on experience operating automated and semi-automated trading systems under live conditions: monitoring, tuning, and intervening when it matters Strong analytical instincts: you can take a messy dataset of fills and quotes and turn it into a concrete execution improvement A deep, intuitive grasp of market microstructure and the ability to explain why a strategy works, not just that it does Proficiency in Python for analysis, tooling, and interaction with trading systems An ownership mindset: being p

ABOUT CUBIST Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. WHAT YOU'LL DO The Quant Developer will be responsible for building and maintaining the research infrastructure and backtesting frameworks that support quantitative research, working closely with researchers to translate research ideas into robust, scalable, and maintainable research systems. The role spans multiple areas, including system design, data pipeline development, and the development of research and backtesting frameworks. WHAT'S REQUIRED Background in Electrical Engineering, Computer Science, or a related field, with 3+ years of software development experience as a software engineer. Strong programming ability in C++ and Python. Solid command of CI/CD practices and tooling, with the ability to design and maintain automated testing and build pipelines for research and backtesting environments. Practical knowledge and hands-on experience with distributed computing and distributed job scheduling / task assignment. Excellent analytical and engineering problem-solving skills. Demonstrated ability to work independently on large datasets and large codebases. A strong team player who works closely with researchers to translate research ideas into stable, maintainable research systems. Willingness to take ownership of your work, able to operate both independently and within a small team, while remaining careful, detail-oriented, and capable of performing well under pressure. Strong English communication skills. Commitment to the highest ethical standards. We take care of our people We invest in our people, their careers, their health, and their well-being. When you work here, we provid

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

A Career with Point72's Trading Research Team WHAT YOU'LL DO Build and scale the research-to-trading platform that enables to support the design, testing, and deployment of quantitative strategies from prototype to production Design and implement high-performance analytics and pricing libraries in C++ and Python to support back testing, simulation, and real-time decision making Partner with investment professionals across the global business to translate ideas into robust, production-grade code and reproducible experiments Develop and maintain data pipelines and storage solutions that ingest, validate, and serve large historical and real-time market datasets Deploy, monitor, and operate production services, including automated testing, release processes, and incident response Drive performance and latency optimizations across code paths and infrastructure using profiling and benchmarking techniques Create tooling for experiment management, post-trade analysis, and model validation to measure strategy behavior and market impact Lead and contribute to the technical roadmap, increasing automation, resilience, and scalability of the research infrastructure Mentor junior developers, share best practices for software engineering, and promote a culture of continuous improvement and technical excellence WHAT'S REQUIRED Bachelor’s degree or higher in computer science, engineering, mathematics, physics, or a related quantitative discipline 3+ years of professional software engineering experience building production systems in a collaborative environment Strong proficiency in Python for data analysis and tooling and fluency in modern C++ for performance-sensitive components Practical experience building and querying relational databases or columnar data stores using SQL and hands-on experience with Linux development Proven experience designing and operating production services, including testing, deployment, and monitoring practices Demonstrated ability to profile, debug, and

We are looking for research interns to join our Quantitative Equity team for 4 to 8 months starting in January or May 2027. We are a top-performing quant fund that manages over $111 billion in financial assets, with a track record spanning more than two decades. As a privately owned firm, we take a long-term perspective, investing in lasting business success and the long-term careers of our people. What You Will Do Investing presents a rich set of research problems that you will explore in this role. Quantitative Researchers lead the development of our investment models and strategies. As an intern, you will work on a real investment research project that requires thinking deeply about the factors that determine business success and modeling the complex dynamics of capital markets, including how information is created, interpreted and reflected in prices. Y our work will have a direct impact on investment outcomes. You will own your research project from beginning to end, including idea generation, signal construction, backtesting and calibration. There is plenty of opportunity to collaborate with your peers and receive mentorship from senior members of our research team. Our team works with: State-of-the-art techniques, including reinforcement learning, large language models, AI agents and econometric methods Large financial and alternative data Advanced technologies, such as high-performance computing infrastructure and custom research systems What You Bring Exceptional quantitative and technical ability : a strong foundation in mathematics, statistics, computer science, economics, finance or a related discipline An interest in finance: an interest in the domain is essential ; an understanding of capital markets and the drivers of business success is valuable but not required Evidence of exceptional ability and achievement: demonstrated through academic, professional, research, competition

We are a special software team embedded in a top performing quantitative equity fund that manages over $78+ billion USD in financial assets. This is a fantastic opportunity in the exciting intersection of finance and technology where investment decisions are made using technology. Quantitative equity funds use programmed investment strategies and as a result, our developers are crucial to its success. The team is headquartered and deeply rooted in West Coast Vancouver. We place high value on maintaining an entrepreneurial spirit and creating a culture where each of us has opportunities to succeed. What You Will Do Developers play an essential role through innovative technologies: machine learning, cloud computing, optimization engines, non-traditional high-performance databases, custom applications and data visualization. You own the entire software life cycle: Collaborate with portfolio managers, analysts and researchers to analyze interesting financial problems. Design, plan and implement solutions in an entrepreneurial spirit. Keep investment systems running smoothly through enhancements and support. What You Bring Programming Knowledge – you have an undergraduate, graduate, or post-graduate degree in a computer-related field OR exceptional programming skills gained through your work experience. Deeply Analytical – you possess an analytical mind and enjoy mental challenges. An ability to perform deep thoughtful analysis is required for this role. Passion for Technology – we work with several programming languages (Kdb+/Q, Python, R, Java, C#, Spark) and upfront knowledge is not required. If you are passionate about technology, learning new languages and concepts is natural and fun. Collaborative Communication – you have a collaborative spirit that helps you to work well with others and you communicate effectively. Interest in Investment Management – this is key. Your interest will help you learn about our complex domain. We we