Early Career Software Engineer at Trexquant | New York

Trexquant is a dynamic systematic hedge fund leveraging advanced statistical algorithms to trade equities, futures, and various global markets. Our approach begins with extensive datasets, from which we create comprehensive feature sets and employ diverse machine learning techniques to identify trading signals, culminating in the formulation of market-neutral portfolios. We are on the lookout for innovative data scientists, physicists, engineers, economists, and programmers eager to contribute to the development of cutting-edge machine learning strategies that predict the movements of liquid financial assets with precision.The role of a Quantitative Researcher at Trexquant offers opportunities across several specialized teams:Alpha Researcher:Join the Alpha Researcher team to design and implement market-neutral signals, analyze large datasets, and collaborate with the Data and Strategy Research teams to create a diverse array of predictive models.Data Scientist:As part of the Data Science team, you will work on data parsing and analysis, sourcing new datasets, and teaming up with the Alpha and Strategy teams to build predictive machine learning models.Strategy Researcher:In the Strategy team, you will engage in the development of systematic strategies utilizing various machine learning and statistical methodologies, training and validating data derived from actual market trading.Upon applying for the Quantitative Researcher position at Trexquant, you will first be evaluated on the fundamental skills necessary for the role. Our interview process is designed to help us understand your strengths better and match you with a research team that aligns with your skills and preferences.Your Responsibilities:Design and optimize machine learning models aimed at predicting liquid asset movements using extensive financial datasets and a rich library of trading signals.Analyze data sets for future alpha development.Explore and implement cutting-edge academic research in quantitative finance.Collaborate with skilled quantitative researchers to conduct experiments and validate hypotheses through simulations.Requirements:BS/MS/PhD in a STEM field.Enthusiasm for machine learning.Proficiency in programming languages such as Python.Exceptional problem-solving abilities.Ability to function effectively both independently and as part of a team.Knowledge of financial accounting is advantageous.A background in quantitative finance is beneficial but not a prerequisite.Benefits:Competitive salary plus bonuses based on individual and company performance.

Join our dynamic Futures team as a Quantitative Researcher and leverage your skills in financial modeling and statistical analysis to develop innovative trading models. In this pivotal role, you will engage in research and model development focused on trading and risk management in the futures markets. We are looking for a proactive candidate with a strong grasp of market dynamics and a passion for data-driven decision-making.Key Responsibilities Create, implement, and enhance trading strategies to forecast trends in the futures market using comprehensive financial data and diverse trading signals. Analyze extensive datasets to uncover actionable alpha signals and formulate effective futures trading strategies. Research and apply leading academic insights in quantitative finance to evaluate and optimize the profitability of trading strategies. Drive continuous innovation by integrating new data sources and advanced methodologies to enhance model performance and scalability. Collaborate with a team of skilled quantitative researchers to conduct experiments, backtest theories, and refine strategies through thorough simulations and analytical rigor. Qualifications BS, MS, or PhD in a STEM discipline. A minimum of 2 years of experience in quantitative research, particularly in futures markets. A strong enthusiasm for machine learning and its applications in finance. Expertise in programming languages such as Python and proficiency in statistical modeling techniques. Excellent analytical and problem-solving capabilities. Effective collaboration skills, with the ability to work independently as well as in a team setting.

Trexquant is a systematic fund focused on quantitative finance, with a team of researchers and engineers dedicated to advancing trading operations. The company is investing in its quantitative research and trading platform, aiming to shape the future of systematic trading. This early career Software Engineer role is based in New York and offers the chance to work alongside experienced engineers and quantitative researchers. The position centers on building and improving the infrastructure that supports systematic trading, including data pipelines, backtesting tools, and execution systems. Many projects involve greenfield development, offering opportunities to help design and implement new systems from the ground up. What you will do Develop low-latency, high-throughput research and trading systems using languages such as C++, C, Java, or Rust. Design and optimize data processing pipelines to ensure reliable access to large, high-quality datasets. Help create tools for backtesting, model training, and strategy evaluation. Work with researchers and traders to deliver technical solutions that support research and trading performance. Participate in code reviews, testing, and documentation to maintain high standards. Stay current with new technologies and best practices, contributing ideas to improve systems. Requirements Bachelor's or Master's degree in Computer Science or a related STEM field. Strong grasp of data structures, algorithms, and object-oriented programming. Proficiency in at least one programming language: C++, C, Python, Java, or Rust. Familiarity with Linux environments. Strong problem-solving skills and the ability to learn quickly in a team setting. Benefits Competitive salary with performance-based bonuses. Supportive and friendly workplace culture. Full coverage of PPO health, dental, and vision insurance premiums for employees and dependents. Pre-tax commuter benefits. Weekly company meals. Compensation The base salary range for this role is $130,000 to $175,000, depending on educational and professional background. Compensation may also include a discretionary, performance-based bonus. This position is overtime-exempt. Applications are open for both Stamford and New York City offices. The New York office is expected to open in October 2026. Trexquant is an Equal Opportunity Employer.

Trexquant is on the lookout for an exceptional Senior Data Architect to spearhead the design and implementation of a cutting-edge architecture for our research and simulation data ecosystem. This pivotal role will unify Trexquant’s vast array of datasets—sourced from numerous vendors—into a streamlined, efficient, and scalable data platform that caters to simulation, research, and alpha generation across diverse asset classes.The ideal candidate will construct the comprehensive data infrastructure that empowers researchers and simulators to effortlessly discover, query, and integrate datasets spanning equities, futures, FX, ETFs, corporate bonds, and options. This role entails designing effective data models, storage solutions, and user-friendly interfaces that facilitate the transformation of raw vendor data into structured, analysis-ready formats, thereby enhancing systematic research and robust backtesting.ResponsibilitiesDesign and execute a unified data platform that consolidates hundreds of vendor datasets, ensuring consistent, accessible, high-quality data for simulators and researchers.Create efficient storage and retrieval systems to enable large-scale historical backtesting and high-frequency research workflows.Develop user-friendly interfaces and APIs that facilitate easy variable discovery, metadata exploration, and data assembly into standardized stocks × values matrices for rapid hypothesis testing.Work collaboratively with quantitative researchers and simulation teams to grasp their workflows, ensuring the data platform meets analytical and performance needs in real-world scenarios.Establish best practices for data modeling, normalization, versioning, and quality control across various asset classes and data vendors.Collaborate with infrastructure and DevOps teams to enhance data pipelines, caching mechanisms, and distributed storage for improved scalability and reliability.Prototype and deploy internal data applications aimed at bolstering research productivity and data transparency.Guide and mentor data engineers to uphold robust, maintainable, and well-documented data systems.

At Trexquant, a cutting-edge systematic hedge fund, we leverage a multitude of statistical algorithms to navigate global equity, futures, and other markets. Our approach harnesses extensive datasets to create comprehensive feature sets, utilizing advanced machine learning techniques to unearth trading signals and integrate them into market-neutral portfolios. We are actively seeking talented individuals from diverse backgrounds, including data science, physics, engineering, economics, and programming, to pioneer the next wave of machine learning strategies that adeptly forecast the movements of liquid financial assets.As a Quantitative Researcher, you will engage in the development of market-neutral signals, meticulously parse and analyze large datasets, and collaborate with the Data and Strategy Research team to construct a variety of predictive models. While we welcome expertise across all asset classes, our immediate focus lies on equities, futures, commodities, and event-driven research.

Join our dynamic Volatility team at Trexquant as a highly skilled Quantitative Researcher. This crucial role involves collaborating closely with the Head of Volatility to expand our research group's capabilities, focusing on the development of specialized volatility tools and the exploration of trading signals and strategies within the volatility markets. The ideal candidate will possess a strong background in volatility modeling, statistical analysis, and a comprehensive understanding of market dynamics.Key Responsibilities:Develop and maintain proprietary pricing and analytics tools tailored for volatility research.Calibrate implied volatility surfaces across a range of options including single stock, index, and ETF options, while working with developers to implement models into backtesting and live trading systems.Design, implement, and enhance trading strategies aimed at predicting volatility market trends using extensive financial datasets and diverse trading signals.Analyze large datasets to uncover actionable alpha signals and devise effective volatility trading strategies.Investigate and leverage innovative academic research in quantitative finance to evaluate, enhance, and maximize the profitability of trading strategies.Continuously refine existing models by incorporating new data sources and advanced methodologies to improve performance and scalability.Collaborate with a team of seasoned quantitative researchers to conduct experiments, backtest hypotheses, and fine-tune strategies through comprehensive simulations and data analysis.

Join Trexquant as a dedicated Linux Systems Engineer, where you will play a pivotal role in constructing, managing, and scaling our on-premise infrastructure. This hands-on position emphasizes bare-metal Linux systems and offers significant ownership of server provisioning, storage management, and overall system reliability.The ideal candidate will be meticulous, highly disciplined, and adept at thriving in a challenging, production-critical environment. This role is specifically tailored for individuals with extensive experience in physical infrastructure, Linux internals, and automation within a high-performance context.Key Responsibilities:Construct, provision, and manage bare-metal Linux servers, overseeing OS installation, configuration, and lifecycle management.Take full ownership of server infrastructure from hardware through to the operating system and core services, ensuring optimal stability and performance.Configure and manage storage systems, including ZFS and enterprise storage platforms (e.g., NetApp, Dell, or similar).Monitor system health and performance, troubleshoot issues, and implement sustainable long-term solutions.Develop and maintain automation scripts using Ansible and Bash to standardize provisioning, configuration, and operational procedures.Conduct system patching, upgrades, and capacity planning across an expanding server fleet.Engage in incident response and root cause analysis, focusing on the continuous improvement of system reliability.Collaborate with engineering and infrastructure teams to optimize application performance on Linux systems.Contribute to documentation, runbooks, and operational best practices.Support data center operations as required, including hardware troubleshooting, racking, cabling, and server replacements.Occasionally travel to data centers for maintenance, expansions, and problem resolution.

Trexquant is hiring a Senior Data Architect to lead the creation of a new data platform for quantitative research and simulation. This role centers on building a scalable system that unifies data from hundreds of vendors, ensuring reliable and accessible information for research and alpha generation across multiple asset classes. Key Responsibilities Design and implement a data platform that consolidates vendor datasets, offering consistent, high-quality access for research and simulation teams. Develop storage and retrieval solutions to support large-scale historical backtesting and high-frequency research. Create user-friendly interfaces and APIs, enabling researchers to discover variables, review metadata, and assemble standardized datasets for rapid idea testing. Work closely with quantitative researchers and simulation teams to understand their requirements and ensure the platform meets analytical and performance needs. Set standards for data modeling, normalization, version control, and quality assurance across diverse asset classes and sources. Partner with infrastructure and DevOps teams to enhance data pipelines, caching, and distributed storage for improved scalability and reliability. Prototype and launch internal tools that improve research efficiency and data transparency. Mentor data engineers, supporting well-documented and maintainable data systems. Platform Scope The platform will handle data for a broad range of financial instruments, including equities, futures, FX, ETFs, corporate bonds, and options. The focus is on transforming raw vendor feeds into structured, analysis-ready datasets that enable systematic research and backtesting. Location This position is based in New York, New York, United States.

Trexquant is a premier systematic hedge fund that employs cutting-edge machine learning and quantitative strategies to maintain a market-neutral portfolio. With a global presence spanning the U.S., China, and India, our innovative team of researchers, technologists, and finance experts is dedicated to advancing the field of quantitative finance.We are on the lookout for a motivated and detail-oriented Business Development and Strategy Associate to enhance our growing statistical arbitrage hedge fund. In this role, you will collaborate closely with the Chief Strategy Officer to identify new business opportunities, implement initiatives for process and product improvements, and drive the firm's growth through data-centric decisions. The ideal candidate will demonstrate robust analytical and project management abilities, along with an entrepreneurial mindset to expand our market presence and reinforce our competitive advantage.

Join Trexquant as an AI Research Engineer, where you will be at the forefront of creating AI-powered systems that enhance alpha discovery for a forward-thinking quantitative hedge fund. In this pivotal role, you'll utilize state-of-the-art AI coding tools, such as Claude Code and other LLM-based agents, to develop automated research workflows that yield innovative data variables, predictive signals, and systematic trading strategies.Your work will bridge quantitative research, machine learning, and AI-enhanced development, resulting in scalable systems that significantly boost research efficiency and the quality of investment ideas.Key ResponsibilitiesDevelop AI-assisted research pipelines for data ingestion, feature engineering, alpha generation, and backtesting.Create autonomous workflows that explore datasets and propose potential signals.Quickly prototype and assess systematic strategies using comprehensive validation frameworks.Enhance research productivity by integrating AI coding agents into the quantitative workflow.Collaborate with researchers and Portfolio Managers (PMs) to transition validated alpha signals into production-ready applications.QualificationsProficiency in Python programming with experience in building research infrastructure.Strong foundation in statistics, machine learning, and backtesting methodologies.Practical experience utilizing AI coding tools (e.g., Claude Code, GPT-based agents) within a development workflow.Background in quantitative research, systematic trading, or alpha signal development is preferred.BenefitsCompetitive salary with performance-based bonuses.Friendly and collaborative work environment.Comprehensive PPO health, dental, and vision insurance fully covered for you and your dependents.Pre-tax commuter benefits.Weekly company meals.Applications are welcomed for both Stamford and New York City offices, with the NYC location set to open in October 2026.The base salary for this position ranges from $175,000 to $200,000, determined by the candidate’s educational background and experience. This role is classified as overtime-exempt.Trexquant is proud to be an Equal Opportunity Employer.

About the PositionJane Street is seeking talented Quantitative Researchers to assist in developing models, strategies, and systems for pricing and trading financial instruments. You will collaborate closely with seasoned researchers dedicated to mentoring our newest team members, immersing yourself in experimental design, dataset generation, time series analysis, feature engineering, and model construction for financial datasets.At Jane Street, our researchers, engineers, and traders work in close proximity, fostering a collaborative environment to train models, design systems, and execute trading strategies. We leverage petabytes of data and operate on a computing cluster with hundreds of thousands of cores, alongside a rapidly expanding GPU cluster featuring tens of thousands of high-performance GPUs. Your daily tasks may include delving into market data, fine-tuning hyperparameters, debugging distributed training performance, or analyzing our model's trading behavior in production settings.We reject the notion of a “one-size-fits-all” modeling approach; instead, we embrace a wide array of statistical and machine learning techniques, from linear models to deep learning, adapting our methods to meet the specific needs of each problem. The most successful researchers thrive on their curiosity about how their contributions integrate into the broader framework of our trading operations, transforming their findings into actionable strategies.About YouIf you’ve never considered a career in finance, you’re not alone—many of our team members were in the same boat before joining us. If you possess a curious mind and a passion for tackling intriguing challenges, you will likely feel at home here. Ideal candidates will:Utilize logical and mathematical reasoning to approach diverse problemsExhibit intellectual curiosity; eager to ask questions, acknowledge mistakes, and pursue new knowledgeBe proficient in programming, particularly with PythonCommunicate precisely and think openly, enjoying collaboration with colleagues across various fields and expertiseWhile most candidates have a background in data science or machine learning, we prioritize your thought process and learning capability over specific knowledge. A PhD or relevant research experience is advantageous.For more insights, feel free to explore our interview process and meet some of the team.

Our MissionAt comity, we are dedicated to revolutionizing energy systems by enhancing their reliability, transparency, and efficiency. Our goal is to pave the way for a future characterized by sustainable and abundant energy. To achieve this, we employ cutting-edge statistical learning and convex optimization techniques (AI) to construct the financial frameworks essential for tomorrow's energy systems.We envision a world where energy systems are efficient, autonomous, resilient, and powered entirely by renewable energy sources. About UsFounded by industry veterans from Apple, Bluevine, Affirm, Square, and Google, our leadership team comprises Stanford alumni who possess deep expertise in complex systems, machine learning, and structured finance. Supported by esteemed investors like Maverick Ventures and Caffeinated Capital, we are aligned with our strategic objectives and vision for the platform.Your RoleWe are seeking a Quantitative Researcher for Monetization to assist in designing, deploying, and operating autonomous, systematic strategies that extract economic value from our future information (forecasts) and energy systems models, while navigating real-world market constraints. In this role, you will:Identify and prioritize market opportunities based on potential value and complexity.Architect end-to-end autonomous strategies encompassing models, forecasts, and market actions.Enhance strategy performance by utilizing metadata to inform bidding decisions.Manage the full process from information development to production-ready code, stepping in when additional resources are needed.What We Value in YouYou have applied stochastic optimization to challenges within financial or electrical engineering, operations research, or economics.You possess a strong conceptual understanding of probability theory and an aptitude for shaping and managing distributions.You bring over 5 years of design, research, and development experience within the industry.You have a profound understanding of the dynamics and structure of energy, commodity, or financial markets.You are proficient in developing and monitoring machine learning models.You are a skilled programmer, particularly in Python.Most importantly, you are driven and passionate about making a significant impact in the energy sector.

Forge Global is expanding its Research & Data Analytics team in New York. The company builds technology and data solutions for private markets, supporting innovation across industries from space exploration to artificial intelligence. Forge’s marketplace and liquidity tools help employees, employers, and investors access and manage private company shares. Role overview The Quantitative Researcher will play a key part in producing original research and strengthening Forge’s analytics capabilities. This position involves working with proprietary private market data, analyzing macroeconomic trends, and identifying emerging themes that matter to clients and stakeholders. The research produced will support clients, prospective clients, internal teams, and public audiences. What you will do Generate original research using exclusive private market data Analyze macro trends and new themes relevant to private markets Create insights and content for clients, internal partners, and public audiences Contribute to the ongoing development of Forge’s Research & Analytics functions What Forge values Boldness in pursuing new ideas and solutions Accountability in delivering accurate, impactful research Humility in collaborating with colleagues and clients

About BasisBasis is a pioneering nonprofit organization dedicated to applied AI research, driven by dual objectives that enhance each other.Our primary focus is to understand and construct intelligence. This encompasses establishing the fundamental mathematical principles of reasoning, learning, decision-making, comprehension, and explanation, alongside developing software that embodies these principles.Secondly, we aim to empower society to tackle complex challenges. This involves broadening the scale, complexity, and scope of problems we can currently address and, crucially, accelerating our future problem-solving capabilities.To realize these ambitions, we are establishing an innovative technological framework inspired by human reasoning and fostering a collaborative environment that prioritizes human values.About the RoleAs a Research Engineer, you will play a vital role in advancing Basis’ mission by converting research concepts into accurate, robust, and scalable high-quality code.We are looking for technically proficient individuals who are enthusiastic about delving deep into foundational concepts. Our research engineers are committed to conducting rigorous, high-quality science, unafraid to experiment, learn from mistakes, and explore innovative ideas.Basis thrives on collaboration, both within our team and with external partners. We seek individuals who enjoy tackling challenges greater than they can manage alone.Machine Learning Research Engineer Focus AreasThis position is aimed at experts in machine learning engineering. Key areas of focus include:Probabilistic programming and statistical inferenceDeep learningCausal inferenceProgram synthesis and analysisML Ops and systems engineeringThese areas will be explored in the context of developing reasoning systems. Research engineers will also engage with topics including programming language design and implementation, automatic differentiation, and SAT/SMT solvers.

About BasisBasis is a nonprofit organization dedicated to applied AI research, striving to achieve two interconnected objectives.Firstly, we aim to understand and develop intelligence. This involves establishing the mathematical foundations of reasoning, learning, decision-making, comprehension, and explanation; along with creating software that embodies these principles.Secondly, we seek to enhance society's capacity to address complex challenges. This means broadening the range, scale, and intricacies of the problems we can tackle today, while also accelerating our ability to solve future challenges.To fulfill these missions, we are constructing a novel technological framework inspired by human reasoning, and fostering a collaborative organization that prioritizes human values.About the RoleAs a Research Scientist, you will spearhead Basis's initiatives to deepen our comprehension of the theoretical, mathematical, and computational aspects of intelligence.We seek individuals with exceptional technical skills who are passionate about exploring concepts at their core. Our research scientists and engineers are committed to conducting rigorous, high-quality, and robust scientific inquiry, yet they embrace experimentation, learning from mistakes, and exploring innovative ideas to achieve their goals.Basis thrives on collaboration, both internally and with external partners; thus, we value team players who relish tackling challenges that surpass individual capabilities.Research FocusOur research under the MARA project is dedicated to forging new principles and technologies for modeling, abstraction, and reasoning in AI systems. The primary aim of MARA is to reveal principled methodologies for how intelligence constructs, refines, and applies world models through interactive experimentation.For this position, we specifically seek experts in Reinforcement Learning & Planning who can push the boundaries of model-based RL, exploration strategies, optimal control, and Bayesian optimization. You will develop agents capable of learning efficient policies in intricate, partially observable environments by utilizing structured world models.

Overview: Join Guidepoint's dynamic Market Research Team as the Director of Quantitative Panel, where you will spearhead the growth, management, and maintenance of our expert research community for quantitative surveys. This pivotal role involves crafting outreach strategies, ensuring panel quality and health, and overseeing custom recruitment operations to enhance our panelist experience. This is a hybrid role based in our New York office, with an option for full remote work. Key Responsibilities: Lead the management of Guidepoint’s quantitative survey panel community, focusing on database administration, respondent engagement, retention metrics, and customized recruitment strategies. Collaborate with both internal and external vendors to create tools and systems for feasibility assessments in research and project bidding for quantitative survey initiatives. Provide strategic direction on panelist engagement, optimizing both email outreach and alternative invitation methods to enhance community participation. Partner with IT/Engineering to ensure seamless integration between Guidepoint’s expert network and quantitative respondent databases, maintaining data accuracy and comprehensiveness. Work alongside the Advisor Relations team to develop a response strategy and playbook addressing survey-related advisor concerns, including technical issues, survey satisfaction, and incentive management. Oversee the expansion of the panel through custom recruitment efforts, managing both personnel and systems like ContactOut and AggKnowledge to meet project demands and bolster proactive sales capabilities. Ensure panelist quality through effective vetting systems, promptly addressing any quality concerns by quarantining or removing panelists who do not meet established thresholds. Perform additional duties as required. Qualifications: A minimum of 10 years of experience managing an international market research panel or a large membership organization, with a preference for backgrounds in the medical or enterprise B2B sectors. Proficiency in database and contact management utilizing a CRM or market research panel management platform (e.g., Forsta, Qualtrics, RallyUXR) or other SQL-based data management tools. Experience in email marketing, outreach techniques, A/B testing, and campaign optimization. Strong collaboration skills with technical product and engineering teams on data engineering and web development projects. A demonstrated ability to engage with diverse stakeholders and drive community growth and satisfaction.

About the Role The International Crisis Group is seeking a Quantitative Research Intern to join the eEARTH Project. This position supports analysts working on research related to resource-driven conflicts. Interns will gain practical experience in conflict analysis, earth observation, and advocacy within a respected international NGO. Location This internship can be based in New York, USA; Nairobi, Kenya; or Brussels, Belgium. Eligibility Open to students currently enrolled in an academic program who can earn academic credit for the internship Also available to candidates who have secured external funding (such as grants or scholarships) to support their participation Work Arrangement This is a desk-based internship.

Join IMC as a Quantitative Developer, where you will take charge of transforming research into actionable trading strategies. This position uniquely combines research and engineering, allowing for continuous feedback from the initial concept to live trading. Your role will involve creating sophisticated systems that leverage quantitative insights to develop a competitive edge, with direct visibility into the impact of your contributions.

About the FellowshipPostdoctoral Fellowships at Basis provide a unique opportunity for distinguished researchers to advance their expertise in the field of computational intelligence. This encompasses areas such as reasoning, learning, and decision-making. Fellows will collaborate closely with Basis Research Scientists and esteemed Principal Investigators (PIs) from leading academic institutions.About BasisBasis is a nonprofit organization dedicated to applied AI research, driven by two interdependent goals.Our primary aim is to understand and develop intelligence. This involves establishing the mathematical foundations of reasoning, learning, decision-making, comprehension, and explanation; and creating software that embodies these principles.Secondly, we strive to enhance society's capability to tackle complex problems. This entails broadening the scope and complexity of challenges we can address today and, crucially, expediting our future problem-solving abilities.To fulfill these objectives, we are constructing a new technological framework inspired by human reasoning and fostering an innovative collaborative organization that prioritizes human values.How it WorksPostdoctoral Fellows at Basis are jointly mentored and funded by Basis and partner PIs from academic institutions. Fellows will divide their time between Basis and their academic PI's lab, functioning as part of a jointly advised postdoctoral program.Our established partner PIs include: Nada Amin (Harvard), Kevin Ellis (Cornell), Armando Solar-Lezama (MIT), Youssef Marzouk (MIT), and Tom Silver (Princeton).Each Fellow is paired with a mentor from Basis, chosen to align with their research interests and aspirations.Potential Basis mentors possess a wealth of expertise in various fields, ensuring a tailored and enriching mentorship experience.