Markets Quantitative Analyst Jobs

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

JOB DESCRIPTION Point72 Asset Management is seeking a Quantitative Analyst to join its Portfolio Construction & Analytics Team (PCAT) in the Office of the CIO. PCAT’s mandate is to study all drivers of success for Long/Short Equities investment professionals using data, analytics, and models of investor behavior and the market. These analyses are shared with portfolio managers to improve their strategies and with senior management to better allocate capital across investment teams. The ideal candidate is a highly analytical and creative problem-solver who can conduct independent research, work effectively as part of a team, and effectively summarize and communicate findings. RESPONSIBILITES Conduct bottoms-up analysis on the firm’s portfolios to identify strengths and weaknesses in idea generation, trading, and construction Form top-down views on which strategies offer the best risk/reward for the firm Invent new analytics to quantify skill and frameworks to support trade-offs between different sources of skill and risk Quantify market drivers to support pre-trade risk taking and decision making Communicate key findings to the team, PMs, and Co-CIOs Learn to develop in and contribute back to shared code base, reports, and research tools DESIRABLE CANDIDATES 2 or more years of experience in a quantitative research, portfolio management, or risk management role dealing with equities or equities investments Undergraduate, MS or Ph.D. in Finance, Computer Science, Mathematics, Engineering, or Physics, or other quantitative discipline Experience with statistical models and essential methods of quantitative finance Some level of proficiency in quantitative programming (Python preferred) Highly analytical Good interpersonal skills Detail-oriented Self-starter Ability to work cooperatively in a team-oriented, fast-paced environment A commitment to the highest ethical standards and to act with professionalism and integrity Point72 is a leading global

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. The successful candidate will be expected to operate with substantial independence and combine analytical depth with exceptio

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

About the Team At DoorDash, the Data Science and Analytics team uncovers insights and translates them into actionable recommendations that drive decisions across the organisation. Analytics is integral to all areas of DoorDash, and this role sits within the global BizOps Analytics team with a specific focus on the Australia/New Zealand (ANZ) markets. About the Role You will be a key BizOps partner, working closely with the Strategy & Operations team and the ANZ Executive Leadership Team to turn data into actionable insights—with a specific focus on all things Merchant. In this role, you will work to identify and prioritise the local opportunities that matter most for Merchants to grow, operate, and monetize their business with DoorDash. This will cover areas such as merchant availability, menu quality, ads, promos, operational excellence, and more — improving outcomes for both Merchants and DoorDash. This is a hybrid role, with 3 days in-office and 2 days remote. You're excited about this opportunity because you will… Be a first-class thought partner to our Strategy & Operations and Executive teams and help them make decisions on what’s next for DoorDash Provide insights to enable our cross-functional team to understand marketplace dynamics, user behaviours, and long-term trends Use quantitative analysis and the presentation of data to see beyond the numbers and understand what drives our business Build full-cycle analytics experiments, reports, and dashboards using SQL, Python, R, or other scripting and statistical tools Identify and measure levers to help move essential metrics and make recommendations Work backwards from understanding and sizing problems to ideating solutions Produce recommendations and use statistical techniques and hypothesis testing and other experimentation techniques to validate your findings. We're excited about you because you have… 2+ years of experience in data analytics, consulting, or related quantitative roles and a degr

Our mission at Duolingo is to develop the best education in the world and make it universally available. It’s a big mission, and that’s where you come in! At Duolingo, you’ll join a team that cares about educating our users, experimenting with big ideas, making fact-based decisions, and finding innovative solutions to complex problems. You’ll have limitless learning opportunities and daily collaborations with world-class minds — while doing work that’s both meaningful and fun. Join our life-changing mission to develop education for our half a billion (and growing!) learners around the world. Read our blog to learn more. 🧠 You will... Lead a specific feature of the app, seeing it through the entire product development cycle: ideation, specification, development, release, analysis, and iteration Conduct research, analyze market trends and data and develop a product roadmap for a key component of Duolingo’s business (past projects include: teaching Asian languages better, exploring strategy for emerging markets, and product improvements to attract more offline learners) Work closely with UI/UX designers to ensure an excellent user experience Work with engineers to help guide feature development Perform quantitative analysis on features’ performance and find opportunities for optimization ✅ You have... Currently pursuing an MBA or related Master’s degree graduating December 2027 or Spring 2028 Bachelor’s degree in Engineering, Business, Psychology, Design, Computer Science, or related field 3+ years of professional experience as a PM or in highly related areas, such as software engineering, design, data analysis, language learning, or brand management. Ability to utilize knowledge of user insights, data, and statistical analyses to inform decisions An instinct for creating simple and intuitive user experiences Proven ability to learn fast Demonstrated ability to be resourceful and innovative Experience leading projects and teams A d

ROLE We are passionate about data. We collaborate to build elegant, effective, scalable and highly reliable solutions to empower predictive modelling in finance. Cubist’s Data Services (CDS) group is looking for a Data Scientist to join our dedicated data team. Our group is responsible for the timely delivery of comprehensive and error-free data to some of the most demanding and successful systematic Portfolio Managers in the world. As a Senior Data Scientist in the team, this individual will play a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure, and the live production trading of billions of dollars of capital across global capital markets, including equities, futures, options and other financial instruments. RESPONSIBILITIES Onboarding novel datasets from a huge variety of sources into our platform Building processes, tools and frameworks to ingest, clean and deliver datasets Analysis of data for usability, cleanliness, feature extraction and proposed usage by investment teams Creation of in-house, value added, derived data products for consumption by investment teams Engaging with vendors and internal stakeholders to understand characteristics of datasets Partnering closely with investment teams to ensure their data requirements are met Research on new technologies (including AI solutions) to continuously improve data management and value-add for investment teams REQUIREMENTS PhD or Masters in Financial Engineering, Statistics, Computer Science or other disciplines involving rigorous quantitative analysis Strong programming skills in Python and SQL Experience working with AWS, Linux and Airflow preferred but not required 5+ years of experience as a Data Scientist or similar role Experience working with large data sets including predictive modeling Financial industry experience preferred but not required Strong organization, communication and interpersonal skills Intellectua

ROLE We are passionate about data. We collaborate to build elegant, effective, scalable and highly reliable solutions to empower predictive modelling in finance. Cubist’s Data Services (CDS) group is looking for a Data Scientist to join our dedicated data team. Our group is responsible for the timely delivery of comprehensive and error-free data to some of the most demanding and successful systematic Portfolio Managers in the world. As a Senior Data Scientist in the team, this individual will play a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure, and the live production trading of billions of dollars of capital across global capital markets, including equities, futures, options and other financial instruments. RESPONSIBILITIES Onboarding novel datasets from a huge variety of sources into our platform Building processes, tools and frameworks to ingest, clean and deliver datasets Analysis of data for usability, cleanliness, feature extraction and proposed usage by investment teams Creation of in-house, value added, derived data products for consumption by investment teams Engaging with vendors and internal stakeholders to understand characteristics of datasets Partnering closely with investment teams to ensure their data requirements are met Research on new technologies (including AI solutions) to continuously improve data management and value-add for investment teams REQUIREMENTS PhD or Masters in Financial Engineering, Statistics, Computer Science or other disciplines involving rigorous quantitative analysis Strong programming skills in Python and SQL Experience working with AWS, Linux and Airflow preferred but not required 5+ years of experience as a Data Scientist or similar role Experience working with large data sets including predictive modeling Financial industry experience preferred but not required Strong organization, communication and interpersonal skills Intellectua

ROLE We are passionate about data. We collaborate to build elegant, effective, scalable and highly reliable solutions to empower predictive modelling in finance. Cubist’s Data Services (CDS) group is looking for a Data Scientist to join our dedicated data team. Our group is responsible for the timely delivery of comprehensive and error-free data to some of the most demanding and successful systematic Portfolio Managers in the world. As a Data Scientist in the team, this individual will play a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure, and the live production trading of billions of dollars of capital across global capital markets, including equities, futures, options and other financial instruments. RESPONSIBILITIES Onboarding novel datasets from a huge variety of sources into our platform Develop, test and deploy data pipelines, applications and services Re-shaping, aggregating, enhancing and creating features from datasets Engaging with vendors and internal stakeholders to understand characteristics of datasets Defining and automating qualitative data alerts and reports Partnering closely with investment teams to ensure their data requirements are met Perform preliminary analysis and research to be shared with investment teams REQUIREMENTS Masters in Financial Engineering, Statistics, Computer Science or other disciplines involving rigorous quantitative analysis Strong programming skills in Python and SQL Experience working with AWS, Linux and Airflow preferred but not required Financial industry experience preferred but not required Strong organization, communication and interpersonal skills Attention to detail and a love of processes Strong oral and written communication skills Ability to exercise sound judgment in assessing and determining how to handle queries, calls and issues Ability to multitask and prioritize assignments Commitment to the highest ethica

ROLE We are passionate about data. We collaborate to build elegant, effective, scalable and highly reliable solutions to empower predictive modelling in finance. Cubist’s Data Services (CDS) group is looking for a Data Scientist to join our dedicated data team. Our group is responsible for the timely delivery of comprehensive and error-free data to some of the most demanding and successful systematic Portfolio Managers in the world. As a Data Scientist in the team, this individual will play a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure, and the live production trading of billions of dollars of capital across global capital markets, including equities, futures, options and other financial instruments. RESPONSIBILITIES Onboarding novel datasets from a huge variety of sources into our platform Develop, test and deploy data pipelines, applications and services Re-shaping, aggregating, enhancing and creating features from datasets Engaging with vendors and internal stakeholders to understand characteristics of datasets Defining and automating qualitative data alerts and reports Partnering closely with investment teams to ensure their data requirements are met Perform preliminary analysis and research to be shared with investment teams REQUIREMENTS Masters in Financial Engineering, Statistics, Computer Science or other disciplines involving rigorous quantitative analysis Strong programming skills in Python and SQL Experience working with AWS, Linux and Airflow preferred but not required Financial industry experience preferred but not required Strong organization, communication and interpersonal skills Attention to detail and a love of processes Strong oral and written communication skills Ability to exercise sound judgment in assessing and determining how to handle queries, calls and issues Ability to multitask and prioritize assignments Commitment to the highest ethica

The Trading team develops and operates quantitative trading strategies across prediction markets, equity markets, and crypto markets, including spot and derivatives. We are looking for an experienced Systematic Trader to develop, operate, and continuously improve systematic strategies in fast-moving electronic markets. Responsibilities: Operate and manage systematic trading strategies and frameworks across prediction markets, equities, and crypto, including spot, perpetuals, futures, options, and other derivatives. Monitor live trading, P&L, positions, risk, and execution performance. Research, backtest, deploy, and improve systematic trading strategies. Identify new trading opportunities across markets, products, exchanges, and venues. Analyze strategy and execution performance, including fills, slippage, adverse selection, transaction costs, and latency. Optimize strategy parameters, position sizing, execution, and risk controls. Work closely with quantitative developers and researchers to implement new strategies and improve trading systems. Participate in local trading coverage and rotating weekend coverage. Requirements: 4+ years of experience in systematic, quantitative, electronic, proprietary, or market-making trading. Demonstrated experience developing, operating, or improving profitable trading strategies. Strong understanding of market microstructure, execution, and risk management. Strong Python programming and quantitative data-analysis skills. Experience working with large market and trading datasets; SQL experience is preferred. Strong analytical and problem-solving skills, with the ability to take ownership in fast-moving markets. Master's or PhD degree in a quantitative discipline, or equivalent relevant quantitative experience. Preferred: Experience trading in one or m

The Trading team develops and operates quantitative trading strategies across prediction markets, equity markets, and crypto markets, including spot and derivatives. We are looking for an experienced Systematic Trader to develop, operate, and continuously improve systematic strategies in fast-moving electronic markets. Responsibilities: Operate and manage systematic trading strategies and frameworks across prediction markets, equities, and crypto, including spot, perpetuals, futures, options, and other derivatives. Monitor live trading, P&L, positions, risk, and execution performance. Research, backtest, deploy, and improve systematic trading strategies. Identify new trading opportunities across markets, products, exchanges, and venues. Analyze strategy and execution performance, including fills, slippage, adverse selection, transaction costs, and latency. Optimize strategy parameters, position sizing, execution, and risk controls. Work closely with quantitative developers and researchers to implement new strategies and improve trading systems. Participate in local trading coverage and rotating weekend coverage. Requirements: 4+ years of experience in systematic, quantitative, electronic, proprietary, or market-making trading. Demonstrated experience developing, operating, or improving profitable trading strategies. Strong understanding of market microstructure, execution, and risk management. Strong Python programming and quantitative data-analysis skills. Experience working with large market and trading datasets; SQL experience is preferred. Strong analytical and problem-solving skills, with the ability to take ownership in fast-moving markets. Master's or PhD degree in a quantitative discipline, or equivalent relevant quantitative experience. Preferred: Experience trading in one or m

The Trading team develops and operates quantitative trading strategies across prediction markets, equity markets, and crypto markets, including spot and derivatives. We are looking for an experienced Systematic Trader to develop, operate, and continuously improve systematic strategies in fast-moving electronic markets. Responsibilities: Operate and manage systematic trading strategies and frameworks across prediction markets, equities, and crypto, including spot, perpetuals, futures, options, and other derivatives. Monitor live trading, P&L, positions, risk, and execution performance. Research, backtest, deploy, and improve systematic trading strategies. Identify new trading opportunities across markets, products, exchanges, and venues. Analyze strategy and execution performance, including fills, slippage, adverse selection, transaction costs, and latency. Optimize strategy parameters, position sizing, execution, and risk controls. Work closely with quantitative developers and researchers to implement new strategies and improve trading systems. Participate in local trading coverage and rotating weekend coverage. Requirements: 4+ years of experience in systematic, quantitative, electronic, proprietary, or market-making trading. Demonstrated experience developing, operating, or improving profitable trading strategies. Strong understanding of market microstructure, execution, and risk management. Strong Python programming and quantitative data-analysis skills. Experience working with large market and trading datasets; SQL experience is preferred. Strong analytical and problem-solving skills, with the ability to take ownership in fast-moving markets. Master's or PhD degree in a quantitative discipline, or equivalent relevant quantitative experience. Preferred: Experience trading in one or m

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. SoFi’s Credit team manages credit risk activities for our lending products (Student Loan Refinance, Private Student Loan, Personal Loan, Credit Card, and Mortgage) - including credit strategies/policies for new account origination and portfolio management, collections/recovery strategies and operations, and risk and operational data science and analytics. The team designs data-driven strategies to ensure the growth in lending is consistent with the company’s risk appetite and helps create the products and experiences that put our members’ interests first. The Credit Strategy Lead will work in the Credit team and have responsibilities to analyze and evaluate data to develop and propose value-added credit risk strategies and models for SoFi’s lending products, including Personal Loan, Student Loan Refinance, Private Student Loan, and Credit Card. The Credit Strategy Lead will collaborate with cross-functional teams such as Business Units, Capital Markets, Product and Engineering, and use business knowledge and quantitative and analytical skills to drive revenue, control risk, and provide value to the company and consumers. The ideal candidate will possess a data-driven analytics background and the strategic acumen to direct a function that draws strategic insights from data using database and statistical anal

About Us SharkNinja is a global product design and technology company, with a diversified portfolio of 5-star rated lifestyle solutions that positively impact people’s lives in homes around the world. Powered by two trusted, global brands, Shark and Ninja , the company has a proven track record of bringing disruptive innovation to market and developing one consumer product after another has allowed SharkNinja to enter multiple product categories, driving significant growth and market share gains. Headquartered in Needham, Massachusetts with more than 4,100 associates, the company’s products are sold at key retailers, online and offline, and through distributors around the world. AI at SharkNinja At SharkNinja, we’re building an AI-native culture. We’re not waiting for the future; we’re creating it. Our people are expected to experiment boldly, adopt new tools, and continuously raise what’s possible to create meaningful impact for our consumers. If you believe the best way to do your job hasn’t been invented yet, you’ll fit right in. We’re looking for a curious, motivated Consumer Insights Analysts to join our fast-paced team in the future! This is not a current opening however we are eager to find upcoming talent! In this role, you’ll help bring the consumer voice into every stage of product development—supporting research design, analyzing consumer data, and collaborating with cross-functional teams to translate insights into action. At SharkNinja, you won’t just support products that transform everyday life—you’ll grow in a high-performance, innovation-driven culture where your curiosity and contributions matter. Essential Functions: Assist in leading the development and execution of robust qualitative and quantitative research plans to uncover consumer needs , category trends, and whitespace opportunities that inform product innovation and business strategy. Help develop and master an und