6,188 Quantitative Researcher jobs in the United States

Our client is looking for a quantitative researcher to work within a low latency machine learning trading team that currently researches and builds low latency trading models in the liquid futures space. The candidates primary responsibilities will include researching and implementing fully automated systematic futures signals and strategies with short to medium horizon. Suitable candidates will generally have at least 5 years of comparable quantitative research experience.

5+ years of experience researching low latency futures signals and strategies

MSc or PhD from a top institution is preferred

Strong preference for advanced degrees in a cutting edge quantitative field

Excellent understanding of probabilities, statistics and optimization

Experience manipulating large datasets, including tick-level data

Excellent programing skills: experience with both high-level - either Python, R, Julia as well as a lower-level languages - C or C++

NYC or SF Bay area

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Our client was founded over 27 years ago by technologists to build the fastest, high-frequency trading platform in the world. Based in New York City, they have a footprint in eleven major metros globally. We are looking for an experienced Quantitative Researcher to be a part of a growing team in the Charleston, SC area who is focused on building their team of the world's best systematic trading and engineering talent. They empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization.

As a Quantitative Researcher in one of our clients' trading teams, you will use their in-house research and trading platform-one of the fastest and most comprehensive in the world-to build and deploy systematic trading strategies. Their researchers use statistical and machine learning techniques to uncover patterns in market behavior used to build predictive models, formalize and solve optimization problems to create trading strategies, and are involved in the entire process from idea generation to production results. This is a new team operating collaboratively, with a rare opportunity to work on challenging problems across the full business scope and have an outsized impact.

You Will:

• Analyzing large data sets of various origins to form and test hypotheses regarding market behavior
• Researching and building statistical models of financial instruments' valuation and returns
• Formalizing and implementing trading strategies and algorithms through solving the appropriate optimization problems
• Building robust and scalable quantitative research methods, tools, and platforms across the full pipeline from data extraction and analysis to model calibration and reporting

• Solid academic background in mathematics, machine learning, computer science, physics, or a similar quantitative field with a strong research experience equivalent to a research-oriented master's degree or ideally a PhD in the field
• Strong quantitative research experience in the systematic trading space, across idea generation, research, deployment, and production analysis, with a track record of delivering impactful results
• Effective programming skills and prior experience building high-quality, scalable software in scripting / dynamic languages such as Python or lower-level languages such as C++, ideally in both
• Ability to communicate clearly and effectively both at a high level and in detail

• 401(k) with company matching
• 5 weeks of paid vacation per year plus 11 paid holidays
• Free breakfast, lunch, and snacks on a daily basis
• Reimbursement for health and wellness expenses
• Free events and workshops
• Donation matching program

Our client is looking for a quantitative researcher to work within a low latency machine learning trading team that currently researches and builds low latency trading models in the liquid futures space. The candidates primary responsibilities will include researching and implementing fully automated systematic futures signals and strategies with short to medium horizon. Suitable candidates will generally have at least 5 years of comparable quantitative research experience.

5+ years of experience researching low latency futures signals and strategies

MSc or PhD from a top institution is preferred

Strong preference for advanced degrees in a cutting edge quantitative field

Excellent understanding of probabilities, statistics and optimization

Experience manipulating large datasets, including tick-level data

Excellent programing skills: experience with both high-level - either Python, R, Julia as well as a lower-level languages - C or C++

NYC or SF Bay area

Name:

Phone Number:

Email Address:

Upload Resume: Upload files in .doc or .pdf format. Max size: 2MB (MS Word document preferred)

Research at GSA Capital means combining creativity, rigour and attention to detail in the design of systematic investment strategies. Quantitative researchers utilise techniques from many branches of applied mathematics and statistics to evaluate large quantities of relevant data and develop models of financial markets with the aim of producing robust trading algorithms based on those models.

If you have outstanding academic credentials and believe you possess relevant attributes to successfully contribute towards the research, implementation and continued development of new and existing strategies, please get in touch.

• Drive innovation in fixed income pricing by developing and refining models for CP+.
• Analyze corporate bond market activity and microstructure to extract actionable insights.
• Own and enhance existing research models, and design new ones from the ground up.
• Collaborate with global product and engineering teams to deliver scalable, data-driven solutions.
• Contribute to thought leadership in pricing analytics and market behavior.

• Proficiency in programming languages and tools commonly used for quantitative analysis and data manipulation, such as R, Python, and SQL.
• 3+ years of experience as a quantitative researcher in Fixed Income markets.
• Deep understanding of fixed income market dynamics and ability to apply quantitative techniques to solve real-world trading problems.
• High Interest in quantitative research and pricing models.
• Experience applying advanced Machine Learning and AI techniques (Deep Learning, Tree based models, Reinforcement Learning).
• Undergraduate or Masters' Degree in a quantitative field (science, engineering, mathematics, or statistics is preferred).
• Strong written and verbal communication skills.
• Highly analytical, flexible, and creative problem solver.
• Well-organized, team-oriented, intellectually curious, and proactive.

• Hybrid Environment: Our employees enjoy a mix of working in the office and from home
• Free Food: We provide free lunch for employees when they are working in the office. Plus, our offices are stocked with snacks
• Paid Time Off: Competitive PTO package including vacation and personal days, sick leave and charity days
• Generous Parental Leave: Up to 20 weeks fully paid leave
• 401(k): Dollar-for-dollar employer match up to $17,500
• Employee Stock Purchase Plan: Employees can purchase MarketAxess common stock at a discount
• Wellness Stipend: We provide employees with up to $K annually towards gym memberships, home office equipment and more
• Onsite Healthcare: We offer convenient access to world-class care through Mount Sinai at our Hudson Yards location
• Tuition Assistance and Professional Development: Benefit from live and on-demand learning, role-specific training, employee-led Lunch and Learns and guest speakers
• Core benefits: Highly competitive medical, dental, and vision programs

Numeus is a diversified digital asset investment firm built to the highest institutional standards, combining synergistic businesses across Alpha Strategies, Trading, and Asset Management.

Numeus was founded by successful executives with decades of experience across the finance, blockchain and technology industries, with a shared passion for digital assets. Our values are grounded in an open approach based on connectivity, collaboration, and partnerships across the digital asset ecosystem. People and technology are at the core of everything we do.

We are looking for a Quantitative Researcher who can help us develop alpha through systematic trading strategies. You will work closely with experienced researchers, traders, and a technology team with deep domain expertise. The digital asset space is young, fast-evolving, and filled with innovative sources of alpha and trading opportunities.

Key Responsibilities:

• Employ a rigorous scientific approach to develop sophisticated investment models and deliver insights into how markets behave
• Apply quantitative techniques, like machine learning, to a vast and innovative array of datasets
• Create and test complex investment ideas and develop algorithms that lead to trading decisions
• Analyze investment model performance and behavior, aiming for constant improvements
• Work closely with our team of experienced developers to translate investment models into production code

• Educational background in technical field, preferably Mathematics, Statistics, Physics or Theoretical Computer Science
• Solid experience in model building, backtesting, parameter optimization routines, execution engine design and performance tracking
• Strong analytical skills; experience working with, and analyzing, large datasets
• Strong mathematical and statistical modeling skills (e.g. time-series)
• Ability to think independently, creatively approach data analysis, and communicate complex ideas clearly
• Basic knowledge of the digital asset space is beneficial, but not required
• Intermediate programming background in Python and C++
• Fluent English speaker
• Ability to travel periodically between our offices in NYC, London and Zug, Switzerland

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.

• Perform rigorous applied research to discover systematic anomalies in equities markets
• Present actionable trading ideas and enhance existing strategies
• Identify short term opportunities in the high frequency/intraday space
• Participate in end-to-end development (i.e. data orchestration, alpha idea generation, simulation, strategy implementation, and performance evaluation)
• Contribute towards the teams research tooling and its efficiency
• Help establish a collaborative mindset and shared ownership

• Bachelors degree or higher in mathematics, statistics, computer science, or similar quantitative discipline
• 3+ years of work experience in systematic alpha research in equities using high frequency/intraday data
• Fluency in data science practices, e.g., feature engineering, signal combining
• Technically comfortable handling large datasets
• Comfortable coding in both C++ and Python in a Linux environment
• Exposure working with cloud computing platforms such as AWS
• Highly motivated and willing to take ownership of his/her work
• Collaborative mindset with strong independent research ability
• Commitment to the highest ethical standards

The annual base salary range for this role is $175,000-$200,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. 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.

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

Jump Operations, LLC seeks Quantitative Researcher II (Multiple Openings) at its facility located at 15 East 26th Street, 3rd Floor, New York, NY 10010. Involved in research projects associated with latency prediction and algorithmic improvement based on requirements provided by our internal trading teams. Determine efficient methods to store and analyze very large amounts of data and develop tools to evaluate of the large volume of market data to help improve trading strategies performance. Involved in investigating and designing data mining and machine learning algorithms and recommending solutions to problems. Conduct research for the purpose of modeling and forecasting future price actions and volatility. Build and expand the current revenue base by developing and exploring new opportunities. Execute and implement quantitative investment strategies. Responsible for developing and supporting a scalable quantitative research framework using Python, C++, and other software systems. Conduct research new methods for capturing risk exposure, evaluating risk/reward and performance attribution across multiple asset classes. Participate in all phases of the software development process for computerized trading applications/models, including requirements analysis, specification generation, application design, software coding and optimization. Design and develop applications based on the business requirements for algorithmic trading. Design, develop and implement high-performance trading applications, ranging from front-end applications to black box systems. Build and enhance market prediction models for portfolios utilizing quantitative problem solving and advanced statistical techniques. Analyze data, creating and evaluating trading strategies.

This position requires a PhD or foreign equivalent in Statistics, Finance, Financial Mathematics, Physics, or related quantitative field, plus 1 year of experience in a statistical analysis related role. Alternatively, will accept a master's or foreign equivalent degree in Statistics, Finance, Financial Mathematics, Physics, or related quantitative field, plus 4 years of experience in a statistical analysis related role.

Additionally, the applicant must have experience with:

• Data Mining
• Machine learning and deep learning (natural language processing)
• Python
• C++ in Linux environment
• Model building skills
• R Programming
• Computer simulation, like Monte Carlo algorithm, Lattice QCD algorithm.

At Tanius we have a high standard. Our people come in each day ready to work hard, adapt to new challenges, and find solutions. We are looking for motivated individuals to develop and test new trading systems. Your role will include using the latest machine learning techniques to analyze mountains of market data and apply them to new and existing trading models.

As a researcher you will work closely with traders and developers to analyze market data and trading strategies, and develop new ways to approach the market.

You need to have a working skillset in programming, preferably python, with some exposure to C/C++ or other compiled languages. On the statistics side, you will need a working knowledge of statistics and linear algebra.

Tanius maintains a large suite of tools to enable fast, iteratable research, including very large on premise clusters for optimization and fitting as well as a suite of programmatic apis to our custom tick database and fitting systems. Whatever research you are doing, we'll be able to help scale it quickly.

This position will be tailored to employ your strengths. We are looking for self-starters with a passion for trading.