Quantitative Trader Developer Jobs

Why Work With Us Solve impactful problems. At Seven Research, our close-knit team unites brilliant minds passionate about pushing technological and scientific boundaries in the global markets. We provide state-of-the-art resources and cultivate intellectual freedom, enabling our people to develop groundbreaking solutions to the most complex challenges of our field. Our collaborative approach celebrates excellence from everyone, regardless of tenure. Your Role Our Quantitative Researchers are the intellectual architects of our trading strategies, responsible for developing sophisticated models that transform complex datasets into actionable insights. You will apply rigorous statistical and machine-learning methodologies to diverse financial datasets, develop innovative approaches to understand risk and returns, and design strategy frameworks leveraging first principles from economics and other fields. What We’re Looking For We seek ambitious and talented problem-solvers with strong quantitative backgrounds. No financial knowledge is expected. Quantitative Researcher candidates should have demonstrated capability in conducting cutting-edge research and analysis. We value team members who communicate clearly, have strong critical analysis skills, and can exercise ownership over projects. If working on challenging quantitative problems in a close-knit setting excites you, we’d love to get to know you. The ideal candidate will possess most of the following: PhD, master’s, or bachelor’s degree in computer science, statistics, physics, or a related quantitative field Intellectual curiosity and passion to uncover the inner workings of the global markets Proven track record developing sophisticated predictive models Strong programming skills, including mastery of Python for data analysis Knowledge of statistical and machine learning modeling frameworks Strong problem-solving skills and research acumen Strong communication skills to articulate complex technical concepts Exper

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. Role: A new Cubist portfolio management team specializing in the systematic trading of equities is looking for a Quant Researcher whose core focus will be working on mid-frequency alpha strategies. Joining the team will provide a unique opportunity to be involved with the early stages of a product launch and develop within a growing team. Responsibilities: Perform rigorous and innovative research to discover systematic anomalies in the equities market End-to-end development, including alpha idea generation, data processing, strategy backtesting, optimization, and production implementation Identify and evaluate new datasets for stock return prediction Maintain and improve portfolio trading in a production environment Contribute to the analysis framework for scalable research Requirements: MS or PhD in a quantitative discipline 0-2 years of professional work experience A background in financial markets is not necessary, but an interest in the field is essential Proven expertise in Python and handling large datasets Fluency in data science practices, e.g., feature engineering. Experience with machine learning is a plus Highly motivated, curious, and critical thinker Collaborative mindset with strong independent research abilities Commitment to the highest ethical standards

Quantitative Researchers are responsible for independently conducting quantitative financial research with a focus on statistical and predictive models. 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. Role Quantitative Researchers are responsible for independently conducting quantitative financial research with a focus on statistical and predictive models. Successful researchers manage all aspects of the research process including methodology selection, data collection and analysis, testing, prototyping, backtesting, and performance monitoring. Desirable Candidates M.S., Ph.D., or Ph.D. candidates in finance, computer science, mathematics, physics, or other quantitative discipline. Programming in any of the following: C++, C#, Java, or Python. Strong analytical and quantitative skills. Keen interest in quantitative research and metrics driven decision making. Demonstrated ability to conduct independent research utilizing large data sets. Detail-oriented. Passion for spotting trends in data. Willingness to take ownership of his/her work, working both independently and within a small team. Ability to work under pressure. Prior experience developing, researching, or implementing quantitative models for equities is preferred, but not required. We will provide training for new researchers without finance backgrounds.

JOB RESPONSIBILITIES A highly collaborative, fast-growing team, Point72 Internal Alpha Capture (IAC) is developing scalable quantitative equity trading signals that leverage rigorous research, state-of-the-art machine learning methods, a broad range of public and proprietary data sources, and unparalleled computing power. We are looking for exceptional students to join us as quantitative researcher interns for Fall 2026, Spring 2027 and Summer 2027. Our interns will work closely with our team, receive comprehensive, in-depth training, and help develop novel signals that may have real impact. You will gain exposure to a variety of activities, which may include: Conducting full pipeline signal research, from ideation, via implementation and backtesting, to eventual application. Adapting and extending existing results in the broad field of machine learning; conducting novel research as needed to potentially develop new signals that may enhance portfolio returns. Analyzing very large data sets to extract features useful for predictive models. Providing research assistance to the team. Helping improve the team’s research infrastructure. DESIRABLE CANDIDATES Masters or PhD candidates in machine learning, computer science, finance, mathematics, or other quantitative disciplines. Demonstrated ability to conduct independent research utilizing machine learning over large, possibly noisy, data sets. Strong analytical and quantitative skills, and detail-oriented mindset. Proficient in Python or C++, and Linux environment. Excellent written and verbal communication skills, willing to proactively engage other team members in helping to foster a highly collaborative, team-oriented research environment. Willing to take ownership of his/her work, working both independently and within a collaborative team. Prior experience in the financial services industry is not required. Commitment to the highest ethical standards. The annual base salary range is $120000.00-$180000.00&n

Point72 is seeking a Quantitative Developer to join its Portfolio Construction and Analysis (PCA) team within the CIO office. ROLE Point72 is seeking a Quantitative Developer to join its Portfolio Construction and Analysis (PCA) team within the CIO office. The PCA team plays a vital role in the Equity L/S business at the firm, collaborating with investment teams to improve net revenue and risk adjusted returns. The Quantitative Developer will build, refine, and maintain an efficient technology infrastructure to enable and support the team’s quantitative research and analytical efforts. The ideal candidate is a smart, self-driven, and creative problem solver with strong technical and quantitative skills. RESPONSIBILITIES Architect, build, refine, and increase automation and robustness of the research infrastructure, including data access, risk modeling, and backtesting components Collaborate with quant researchers to implement framework for automating and presenting analytics, reports, and monitors Collaborate with firm-wide technology teams to deliver analytics and tools to users across the firm DESIREABLE CANDIDATES Undergraduate, Masters, or PhD in Computer Science or other quantitative discipline 3+ years of professional experience developing infrastructure to support an investment team Strong programming skills in Python and SQL Solid background in math/statistics/finance and familiarity with quantitative research methodologies and machine learning algorithms Understanding of and experience with the data ingestion process Ability to contribute to the analytics, quant research, and development process Understanding of portfolio construction is a plus Knowledge of equities is a plus High-energy personality and the ability to manage multiple tasks and deadlines in a fast-paced environment High degree of drive – must be a self-starter Ability to recognize and seize opportunities Depth of skills enabling him/her to perform ad hoc projects and task

Please send CVs to [email protected] with “202 7 KEPL Application” in the subject line. 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. About Our Team: KEPL is a fast-growing team at Cubist Systematic Strategies. We specialize in trading medium-frequency statistical arbitrage strategies with high Sharpe. The team is made up of people from top universities and top tier trading and tech firms. We have an open and collaborative culture, and we value rigorous research and innovative technologies. We are actively expanding into new markets and assets classes. Role: We are looking for full-time quantitative research analysts and software developers to join our fast-growing team and contribute to multiple new initiatives that aim to expand our business. The candidate should have a passion for innovation to solve research and trading problems. In this team, the candidate will gain full-stack exposure and build expertise in multiple aspects of quantitative research and trading. The candidate will play an essential role for the team’s successful expansion. The candidate will also collaborate with other team members to innovate our research infrastructure which will take our research and trading capability to the next level. Responsibilities: Conduct quantitative research to support the team’s investment process. Build technologies that bolster research & trading productivity. Develop, maintain, and improve the production trading capacity. Expand the system to new markets and asset classes. Requirements: Master or PhD degree in math, physics, computer science, engineering, or other related discipline. 1-3 years of prof

Job Description We are seeking a small number of highly talented interns to assist in the development, optimization, and monitoring of our production trading platform and research infrastructure. Interns will work on small, highly collaborative teams. Desirable Candidates Undergraduate or graduate candidates in computer science or engineering Significant experience in Python, C++, C, or Java Serious interest in systems programming (e.g. Linux kernel development, compilers, embedded systems, networking, file systems, debuggers) In-depth understanding of how userland programs run on Linux and interact with the kernel Some basic knowledge of Git, databases (e.g. MySQL), and web development frameworks is a plus Clear, concise, and proactive communicator Detail-oriented Willing to take ownership of his/her work, working both independently and within a small team

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. Role Quantitative researcher to help build out a systematic macro (futures, FX, and vol) strategies. Core focus will be working on mid-frequency alpha strategies. Job Description Develop systematic trading models across FX, commodities, fixed income, and equity markets Alpha idea generation, backtesting, and implementation Assist in building, maintenance, and continual improvement of production and trading environments Evaluate new datasets for alpha potential Improve existing strategies and portfolio optimization Execution monitoring Be a core contributor to growing the investment process and research infrastructure of the team Desirable Candidates Masters or PhD in mathematics, statistics, physics or other quantitative discipline. PhD in statistics or machine learning is a plus Experience in quantitative trading, ideally in FX or futures Experience with alpha research, portfolio construction and optimization Experience building statistical/technical, fundamental, and data driven signals Experience synthesizing predictive signals for both cross-sectional and time-series models Strong experience with data exploration, dimension reduction, and feature engineering Thorough understanding of and comfort using a variety of regression techniques—including OLS, MLS, Ridge, Lasso, and Bayesian inference—as well as techniques for dealing with errors that can occur, such as auto-correlation and heteroskedasticity Experience managing and running risk is a strong plus Proficiency in Python using the machine learning stack—numpy, pandas, scikit-learn, etc. Creative mindset Strong time management abi

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. Role/Responsibilities: We are seeking a quantitative researcher for the Cubist Machine Learning Research group with experience in machine learning, especially recent deep learning and natural language processing technology. Researchers will use a rigorous scientific method to develop sophisticated trading models and shape our insights into how the markets will behave. Successful researchers manage all aspects of the research process including data ingestion and processing, data analysis, methodology selection, implementation and testing, prototyping, and performance evaluation. Researchers will be introduced to industry standard datasets, including understanding which data may be relevant to a certain model or financial problem; how to collect, parse, and clean the data; how to incorporate the data into innovative functional models; how to construct and develop features from raw data; and how to estimate effectiveness of such features. Researchers will also be provided with the opportunity to implement the full breadth of their knowledge and training to actively participate in all stages of research & development of financial models through use of machine learning. Based on experience from working with existing industry-standard models and algorithms, researchers will learn how to construct their own models in order to solve complex financial problems and enhance data prediction capabilities within the financial services industry. Requirements: PhD or PhD candidate in machine learning, computer science, statistics, or a related field Experience with sequential modeling and time

Job Description This is an opportunity for students and researchers of advanced data modeling and statistical learning methods to apply these techniques to market prediction and systematic trading. Job Responsibilities Pre-process (validate, clean, normalize, reduce dimension) very large data sets for model estimation and event studies Identify features and relationships useful for the predictive modeling of market dynamics Desirable Candidates Undergraduate, MS, or PhD candidates in finance, computer science, mathematics, physics, or other quantitative discipline Programming in any of the following: C++, Java, C#, MATLAB, R, Python, or Perl Strong analytical and quantitative skills Demonstrated interest in financial markets and systematic trading Clear, concise, and proactive communicator Detail-oriented Willing to take ownership of his/her work, working both independently and within a small team The annual base salary is $120,000-$180,000 (USD) which will be prorated based on internship start and end date. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.

JOB DESCRIPTION This is an opportunity for students and researchers of advanced data modeling and statistical learning methods to apply these techniques to market prediction and systematic trading. JOB RESPONSIBILITIES Pre-process (validate, clean, normalize, reduce dimension) very large data sets for model estimation and event studies Identify features and relationships useful for the predictive modeling of market dynamics DESIRABLE CANDIDATES MS, or PhD candidates in finance, computer science, mathematics, physics, or other quantitative discipline Programming in any of the following: C++, Java, C#, MATLAB, R, Python, or Perl Strong analytical and quantitative skills Demonstrated interest in financial markets and systematic trading Clear, concise, and proactive communicator Detail-oriented Willing to take ownership of his/her work, working both independently and within a small team

We are not working with external recruiting partners at this time, please apply directly to the role if you have further interest in joining Vise Engineering at Vise has the unique opportunity to use technology to revolutionize the RIA wealth management industry. Team members are given ownership and trust with the understanding that they are supported by industry experts and together can build a best-in-class product. We are a small, high-impact team where everyone has a voice in the development of our product and technology. Vise is seeking a passionate Quantitative Engineer to join our talented engineering team. As we build the future of wealth management, you will partner closely with our investment strategy and core engineering teams, as well as our Chief Investment Officer to build sophisticated investment models which shape our portfolio construction and portfolio insights. You will be responsible for writing production ready quantitative models, using advanced numerical techniques, convex optimization routines and industry leading practices. Our team is deeply curious, with a strong desire to solve problems that have no defined answer. You should feel comfortable reimagining investment management and questioning every market assumption. The ideal candidate thrives in a creative, inventive, and fast-paced startup environment and wants to work with people who are equally passionate about our work and mission. The problems we’re solving as an organization are dynamic and each day brings fresh and exciting challenges. We're interested in people who will react quickly and efficiently when called upon to change or pivot. We work closely with convex optimization techniques and numerical optimizations of various problems. Past exposure in solving complex problems in a numerically optimized way is a plus. What you will own Help to maintain and expand the tax-aware portfolio optimizer using state of the art optimization techniques Develop deep experti

A one-of-a-kind international company operating on the cutting edge of technology. The company has risen to prominence in the HFT (High-frequency trading) industry in recent years, having built one of the greatest teams of developers and data scientists on the market, including a great machine learning expert and top-level data scientist as the company's founder. Our trading activities span across various platforms worldwide, encompassing both traditional and cryptocurrency markets. We are seeking a Quantitative Researcher . The one who embodies intelligence, calmness, and composure. We have a lot of financial data, robust infrastructure, and a highly skilled professional team. WHAT YOU’LL BE DOING: Operate automated latency-sensitive trading systems Monitor the systems’ executions and open positions Adjust system parameters based on market conditions Suggest automation and improvements to the systems Communicate relevant news, market events, and system behavior to team members Stay current with system functionality WHAT WE LOOK FOR IN YOU: 3+ years of algorithmic trading experience A proven track record in the last 2-3 years Having your own trading strategies/ideas 1+ years experience in Python Performs well in a remote/hybrid team with variable, project-based responsibilities NICE-TO-HAVE: Experience with international HFT companies and hedge funds Performance in any quantitative field or contest (hackathons, Olympiads, academic contests, etc.) WHY SHOULD YOU JOIN OUR TEAM? Great challenges with fast feedback loops A welcoming group of highly qualified international professionals Great corporate culture with internal events and surprising commitment to fostering a supportive and empowering environment Cutting-edge hardware and technology Work remotely from anywhere in the world Access any of our global offices anytime Flexible schedule 40 paid days off Competitive salary and performance-based bonuses

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: We are currently seeking a Quantitative Risk Analysis Manager to join the Credit Analytics & Reporting team in the Single-Family division. This position will be tasked with managing a team responsible for reporting and analytics regarding Collateral offerings as well as Collateral model business user supports. The role requires deep understanding of data and current code base, designing analytical approaches for business questions and scenario evaluations, managing data research, analyses and preparation of reports and presentations. Our Impact: Our team is responsible for producing reporting packages to monitor trends and performance. We analyze different test and learn or pilot programs to assess risk of the offerings and create reports to monitor these offerings closely to assess broad roll out. We perform significant user activities for enterprise Collateral models for user acceptance testing and provide feedback. Your Impact: Manage a team of three to four people Complete baseline processes and reports monthly and interpret results as it relates to collateral risk management Follow appropriate controls and standards established to maintain and document for processes & reports. Participate in performing ad-hoc analytics in support of collateral policy Cleanse, manipulate and analyze large datasets using statistical software Collaborate with team members and interact across organizational lines to meet business objectives Qualifications: Degree in

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