Python Developer in New York

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

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team At its core, Stripe is a treasury company, and the Treasury Finance team (TFIN) is key to building the Global Payments and Treasury Network (GPTN). Within TFIN, the FX team collaborates closely with product, engineering, sales, and finance teams to manage Stripe’s Corporate and User related FX risk. This includes creating pricing models to keep pace with product expansion and developing hedging strategies to mitigate the risks to Stripe’s profitability. What you’ll do Stripe supports global commerce across 135+ currencies including digital assets.As a result, Stripe needs to build and maintain platform systems capable of pricing, estimating and hedging the resulting FX exposures. Grounded in an understanding of FX market conventions and dynamics, you will partner with Engineering, Data Science, Product, and Finance to maintain operational rigor today while shaping long-term pricing and hedging strategies. Responsibilities Monitor FX risks, execute trades , reconcile position, and attribute costs Build automated risk monitors, alerting tools, and analytical models using SQL and quantitative coding to enable observability and minimize operational toil Collaborate with Product and Engineering to guide the design and scaling of core FX infrastructure, trade execution flows, and liquidity provider integrations Develop risk-based FX pricing methodologies across products and currency pairs, factoring in volatility, transaction costs

About the Team: A well-established quantitative portfolio management team at Point72 is looking for an experienced quantitative professional in the intraday to mid frequency systematic macro space. The candidate will be given the resources and support to drive the build out and expansion of the quantitative macro business. Role: Perform rigorous and innovative research to develop systematic signals for global macro (futures, FX, etc.) markets Work with price-volume and alternative data at intraday to multiday (up to 2-3 weeks) horizons in the mid-frequency space Participate in the research pipeline end-to-end, including signal idea generation, data processing, modeling, strategy backtesting, and production implementation Work in a team of highly qualified and motivated individuals with access to a cutting-edge research and trading infrastructure and clean datasets Responsibilities: Develop systematic trading models across global futures (equity indices, commodities and fixed income) and/or FX markets Alpha idea generation, backtesting, and implementation Evaluate new datasets for alpha potential Contribute to and enhance portfolio optimization, allocation and risk management processes Help drive the growth of the investment process and research capabilities of the team Assist in building, maintenance, and continual improvement of production and trading environments Requirements: MS or PhD in physics, engineering, statistics, applied math, quantitative finance, or other quantitative fields with a strong foundation in statistics 4+ years of signal research or portfolio management experience in futures markets and/or FX as part of a successful proprietary trading team with a track record Prior professional experience with signal combination, portfolio optimization and risk management Demonstrated proficiency in Python, R, or C/C++. Familiarly with data science toolkits, such as scikit-learn, Pandas Collaborative mindset with strong independent research abilities Commit

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

The Opportunity This is an exciting time at Enigma. We’re on the cusp of releasing our next generation of small business intelligence products built on years of learnings in the space. We are seeking an experienced Data Scientist to join our Entity Resolution team and help shape the trajectory of these products. Your work will directly impact the accuracy, scalability, and predictive capabilities of our data platform, influencing key business decisions for our customers. The Role Data is at the core of Enigma’s product, which makes data science the beating heart of what we ship. As a Data Scientist on the Entity Resolution Team, you will work in a cross-functional team alongside other data scientists, engineers, and business stakeholders. You will own problems end to end–from raw source data, through models and scalable pipelines, to the customer interface. Your impact will be measured by the contributions you make with your team to improve the accuracy of our data and the value of our product to our customers. What You’ll Do Translate customer goals into working solutions, using large-scale data transformation, sound statistics, and high-quality code. Most of our work is in Databricks (both Spark SQL + PySpark), supported by statistical tooling, and by ML/AI where the problem calls for it. Set a high standard for rigorous analysis and model development, grounded in sound statistical practice, so that results are high-quality and reproducible. Treat data as a reflection of the real world, and develop repeatable strategies for validating results against ground truth. Develop techniques to detect gaps in our data, find the source, and close them in a way that improves the product. Apply a data-focused, first-principles approach to problem solving. We value people who bias toward simple and elegant solutions, but who can implement state-of-the-art models and techniques when the problem requires it What Makes This Role Exciting? Technical challenge : Enigma

The Opportunity This is a critical and exciting time at Enigma. Our customers consistently tell us that our data products create tremendous value and are deeply aligned with their most important workflows. As demand grows, we have an urgent opportunity to improve both the intelligence of our data and the systems through which customers access it. We are looking for an experienced Senior/Staff Machine Learning Engineer to join our Match Team and help shape the next generation of Enigma’s customer-facing data products. In this role, you will combine advanced statistical and machine learning research with the engineering systems required to power fast, relevant, and reliable search experiences at scale. This is a uniquely high-impact role sitting at the intersection of information retrieval, ranking systems, semantic search, distributed systems, and customer data delivery. The Role At the core of Enigma’s product is our data, which makes both data science and delivery systems central to what we build. As a Senior/Staff ML Engineer on the Match Team, you will lead efforts that improve the relevance, latency, and scalability of our customer-facing data products. You’ll work across the full lifecycle: framing retrieval and ranking problems, developing models and experimentation strategies, evaluating results using real-world signals, and implementing high-throughput search and retrieval systems. This role is ideal for someone who is excited by both hard ranking/search problems and the systems challenges of turning those solutions into low-latency, production-grade retrieval systems. What You'll Do Develop innovative solutions to complex problems in information retrieval, ranking, semantic search, query understanding, and recommendation systems Build and optimize low-latency, high-throughput search APIs, indexing pipelines, and retrieval systems using Python, Typesense, and AWS Evaluate and evolve our search technology stack, driving technical design decisions across index

Come build what the market has been missing. Octaura is a technology company transforming how some of the world’s largest, least digitized markets operate. In loans and CLOs, trillions of dollars still move through phones, emails, and PDFs because the right infrastructure hasn’t existed — until now. We’re applying AI, real-time data, and modern software design to asset classes long overlooked by fintech. Our platforms turn fragmented information into intelligence, manual workflows into automation, and legacy conventions into scalable market infrastructure. You’ll join a high-impact, collaborative team building the systems these markets need to become more transparent, efficient, and connected. The role in a nutshell The Platform Support Engineer will join Octaura’s Platform Support team to maintain and support the CLO and Loans trading system and other internal applications. They are responsible for ensuring the high levels of availability of the production, demonstration and test systems. They will work in a high-pressure mission critical production environment. The candidate will play a key role in the resolution of any problems in the system in a timely and professional manner. To be successful in this role, the Platform Support Engineer is expected to proactively learn and understand Octaura’s business needs, and develop or implement solutions to meet those needs. To that end, the Platform Support Engineer is expected to demonstrate a proven ability to problem-solve and multi-task. Flexibility is a must, as the schedule may include occasional late night or weekend duties. This is an exciting time for Octaura as we are rapidly growing and are looking for energetic, collaborative and driven thinkers to join us! Please note this role is based out of our NYC office and our current structure is 4 days (Mon-Thurs) in the office, 1 day from home. Desired experience Bachelor’s degree or equivalent w

Please send CVs to [email protected] with “202 7 QR Summer Internship Application” in the subject line. When your application is received, we will consider you for all similar positions at Cubist. About Our Firm: 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. Role / Experience: We are looking for exceptional students to be our quantitative researcher interns for the summer of 2027 . An ideal candidate should have a strong passion and initiative to work in a start-up environment. He/she should have strong analytical skills and be able to solve hard problems rigorously. Our typical intern candidates come from quantitative PhD programs of top US universities. Our internship program offers unique KEPL experience. During the internship, our interns will receive rigorous and comprehensive trainings. They will develop strong research skills through working closely with our full-time researchers on brand new quant trading models with real-world impact. We will consider full-time offers for interns after the internship. Requirements: PhD candidate in math/physics/statistics/EE/CS, or other quantitative fields Strong knowledge of computational math, probability, and statistics Strong analytical skills, with attention to details Good communication skills Willing to work in a fast-paced start-u

Come build what the market has been missing. Octaura is a technology company transforming how some of the world’s largest, least digitized markets operate. In loans and CLOs, trillions of dollars still move through phones, emails, and PDFs because the right infrastructure hasn’t existed — until now. We’re applying AI, real-time data, and modern software design to asset classes long overlooked by fintech. Our platforms turn fragmented information into intelligence, manual workflows into automation, and legacy conventions into scalable market infrastructure. You’ll join a high-impact, collaborative team building the systems these markets need to become more transparent, efficient, and connected. The role in a nutshell The Cloud Operations Engineer is responsible for building out our operations platform, ensuring efficiency through automation, deploying product updates, identifying production issues and implementing strategic integrations that meet our clients’ needs. The ideal candidate will have good communication skills, a well-rounded understanding of Enterprise Architecture, and an automation background with experience running production environments at scale. The candidate will help develop new architectural patterns for emerging products, contribute to environment standardization, develop new monitoring and security tools, and contribute to maintaining operational BAU. This is an exciting time for Octaura as we are rapidly growing and are looking for energetic, collaborative and driven thinkers to join us! Please note this role is based out of our NYC office and our current structure is 4 days (Mon-Thurs) in the office, 1 day from home. Core responsibilities Contribute to operational readiness and platform stability by proactive automation and reactive environment support Develop and maintain a platform of integrated systems and tooling to support Agile and DevOps practices across a diverse set of workflows

Come build what the market has been missing. Octaura is a technology company transforming how some of the world’s largest, least digitized markets operate. In loans and CLOs, trillions of dollars still move through phones, emails, and PDFs because the right infrastructure hasn’t existed — until now. We’re applying AI, real-time data, and modern software design to asset classes long overlooked by fintech. Our platforms turn fragmented information into intelligence, manual workflows into automation, and legacy conventions into scalable market infrastructure. You’ll join a high-impact, collaborative team building the systems these markets need to become more transparent, efficient, and connected. The Role An AI Engineer at Octaura, is a software professional who develops and implements AI-powered applications by integrating trained machine learning models, APIs, and data pipelines into functional software products. You will design, build, deploy, and maintain applied machine learning systems that power critical products and workflows across our platform. This role focuses on taking AI solutions from concept through production—working with large, complex datasets and ensuring models are reliable, explainable, and performant in real-world financial environments. You’ll partner closely with product managers, software engineers, and data teams to solve meaningful business problems, improve market efficiency, and introduce AI responsibly into mission-critical systems. Depending on experience, you may take full ownership of complex AI initiatives and help shape Octaura’s ML architecture and best practices. This role is based out of our New York City office (5 Penn Plaza), with a hybrid schedule of four days in the office (Monday–Thursday) and one day remote (Friday). Key Responsibilities Design, build, and maintain production-grade backend services that power AI/ML capabilities, using Java, Spring Boot, Kafka, Redis, PostgreSQL, an

ABOUT PROPRIETARY RESEARCH On our proprietary research team—Market Intelligence—you’ll partner with our Investment Professionals and Compliance team to uncover insights about companies, industries, and the broader economy through deep fundamental research and applying data science and engineering techniques to alternative data sets. You’ll work alongside a talented team with diverse skills, backgrounds, and perspectives. Our industry researchers, product managers, and data scientists and engineers work together to build compliant research products that answer the questions our investment professionals care about most. We look for other bright, motivated, and collaborative people to join our team and grow with us—more than 90% of the leaders in our group were promoted from within. WHAT YOU'LL DO Senior Data Engineers on the Proprietary Research team design and build solutions that enable investment professionals to effortlessly extract insights from large, complex structured and unstructured data sets. As a senior member of our Data Engineering team, you will help set technical direction and work closely with investment professionals, researchers, and data scientists to design, build, and launch robust end-to-end data pipelines and tools that that help extract the most value out of Point72’s data assets. In this role, you will: Develop and support big data processing pipelines including but not limited to ingestion, transformation, and end-customer delivery Build out cloud-based infrastructure using distributed techniques for other data engineers / data scientists / researchers Be at the forefront of new technology developments with respect to the handling and processing of big data and conduct proof of concepts evaluations of new technologies Build and support visualization and exploration capabilities around our big data sets WHAT EXCITES YOU Technical leadership through hands-on development Having a broad impact on architecture and team processes Transforming

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

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

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team Data Science at Stripe is a vibrant community where data analysts and data scientists learn and grow together. You'll work with some of the most fundamental data at Stripe, and use that data to help drive company-wide initiatives. We have a variety of Data Analytics roles and teams across Stripe and Data Analysts are hired in line with the business needs and domain of the organization they will support. What you’ll do We’re looking for a Data Analyst to partner with Stripe’s Global organization, helping millions of users sell around the world. You’ll help build analytics and data products for solutions such as Adaptive Pricing and Stripe Managed Payments, as well as Stripe’s expansion into new markets across LATAM and EMEA. Responsibilities Design and build scalable data models and infrastructure to power product analytics and metrics reporting as we launch and grow new products Own business-critical data products, including Tier-1 datasets and production pipelines, ensuring reliability through rigorous testing, monitoring, and documentation Build and maintain the metric definitions, metadata, and business context that enable AI agents to help stakeholders explore trusted data and answer business questions independently Develop dashboards, automated reporting, and thoughtful analyses to surface actionable insights and proactively identify business opportunities Partner closely with senior business leaders to translate business needs into ana

JOB DESCRIPTION Researchers are responsible for applying, adapting, and extending existing results in the broad field of machine learning, while also conducting novel research as required. We are interested in all aspects of ML including: predictive modelling, clustering, time series analysis, natural language processing, and computer vision. Successful researchers manage all aspects of the research process including methodology selection, data collection and analysis, implementation and testing, prototyping, and performance evaluation. Some successful researchers have joined us from similar backgrounds at other firms. Others have joined from related fields or directly from academia and have thrived with hands on guidance from our large team of experienced portfolio managers and researchers. Our most exceptional team members combine strong technical skills and a passion for problem solving with an intense curiosity about financial markets and human behavior. DESIRABLE CANDIDATES Students enrolled in a PhD program in machine learning, computer science, statistics, or a related field. Superb analytical and quantitative skills, along with a healthy streak of creativity. Demonstrated ability to conduct independent research utilizing large data sets. Passion for seeing research through from initial conception to eventual application. Curiosity about financial markets Strong scientific programming in Python, R or Matlab. Empirical, detail-oriented mindset. Sense of ownership of his/her work, working well both independently and within a small collaborative team. We’re looking for exceptional colleagues with unparalleled passion. If you’d like your resume to stand out, tell us about your exceptional personal achievements, even if they have nothing to do with finance. Of course we love to hear more about specific engineering or data projects that you’ve worked outside of school, or as part of your curriculum. If you’re proud of the work you did we want to hear abou