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Remote Risk Quant Jobs (NOW HIRING)

Initio Capital

Quantitative Analyst (Quant)

New York, NY · Remote

$145K - $185K/yr

... Remote | New York, NY, United States Quantitative Analyst (Quant) - Initio Capital Location: New ... Risk Management: Collaborate with the risk management team to quantify and assess risk in the ...

Upstart

Senior Manager, Risk Analytics

OR · On-site +1

By establishing and running a centralized, quantitative risk monitoring program for Upstart Bank ... Remote, San Mateo, CA, and Columbus, OH Travel requirements As a digital first company, the ...

Huntington

Model Risk Review Specialist

Westwood, MA · On-site +1

$125.11K - $161K/yr

Communicate to quantitative and business audiences through verbal and written presentations ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

Huntington

Model Risk Review Specialist

Westwood, MA · On-site +1

$125.11K - $161K/yr

Communicate to quantitative and business audiences through verbal and written presentations ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

Huntington

Model Risk Review Specialist

Westwood, MA · On-site +1

$125.11K - $161K/yr

Communicate to quantitative and business audiences through verbal and written presentations ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

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Remote Risk Quant information

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$98K

$169.7K

$259.5K

How much do remote risk quant jobs pay per year?

As of May 29, 2026, the average yearly pay for remote risk quant in the United States is $169,729.00, according to ZipRecruiter salary data. Most workers in this role earn between $134,500.00 and $199,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Risk Quant, and why are they important?

To thrive as a Remote Risk Quant, you need strong quantitative analysis skills, a background in mathematics, statistics, or finance, and typically an advanced degree such as a master's or PhD. Proficiency in programming languages like Python, R, or MATLAB, and familiarity with risk management systems and financial modeling tools are crucial. Exceptional problem-solving, attention to detail, and effective remote communication skills set top candidates apart. These abilities are vital for accurately assessing financial risks, developing robust models, and collaborating efficiently within distributed teams.

What are some common challenges faced by Remote Risk Quants and how can they be managed effectively?

Remote Risk Quants often encounter challenges such as limited access to real-time data streams, maintaining clear communication with on-site teams, and ensuring data security when working offsite. To manage these effectively, it's important to establish robust digital collaboration practices, utilize secure remote access tools, and maintain regular check-ins with stakeholders. Additionally, being proactive in seeking feedback and clarifications helps mitigate misunderstandings and keeps risk analysis aligned with organizational goals.

What are Remote Risk Quants?

Remote Risk Quants are quantitative analysts who work remotely to assess, measure, and manage financial risks for organizations. They use mathematical models, statistical techniques, and programming skills to analyze large datasets and forecast potential risks in investments, portfolios, or financial operations. By working remotely, they collaborate with teams using digital communication tools and often have flexible work arrangements. Their expertise is essential for financial institutions, hedge funds, and corporations to make data-driven risk management decisions.

What is the difference between Remote Risk Quant vs Remote Quantitative Analyst?

AspectRemote Risk QuantRemote Quantitative Analyst
Required CredentialsAdvanced degrees in finance, mathematics, or statistics; certifications like CFA or FRM often preferredSimilar credentials; degrees in math, finance, or engineering; certifications like CFA common
Work EnvironmentFinancial institutions, hedge funds, or risk management firms; primarily analytical and model development rolesFinancial firms, investment banks, or asset management; focus on data analysis and model building
Employer & Industry UsageUsed in risk management, compliance, and regulatory roles within financeUsed in trading, investment analysis, and quantitative research within finance

While both roles require strong quantitative skills and similar educational backgrounds, Remote Risk Quants focus more on assessing and managing financial risks, whereas Remote Quantitative Analysts often concentrate on developing models for trading or investment strategies. The roles overlap but differ mainly in their primary focus within the financial industry.

More about Remote Risk Quant jobs
What cities are hiring for Remote Risk Quant jobs? Cities with the most Remote Risk Quant job openings:
What are the most commonly searched types of Risk Quant jobs? The most popular types of Risk Quant jobs are:
What states have the most Remote Risk Quant jobs? States with the most job openings for Remote Risk Quant jobs include:
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Remote Risk Quant jobs near you
Infographic showing various Remote Risk Quant job openings in the United States as of May 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 100% Remote job distribution, with an average salary of $169,729 per year, or $81.6 per hour.

Senior Quant Developer

Futran Tech Solutions Pvt. Ltd.

Remote

Full-time

Posted 15 days ago

Job description

Senior Quant Developer
Remote USA
Mandatory skills: Python OR C++, Monte Carlo simulation, quantitative background, derivatives pricing models and risk model back testing experience
Skills:
Minimum degree of Master or PhD in quantitative fields is required, with at least 3-5 years of relevant experience.
The candidate must have strong quantitative and analytical background with a solid theoretical foundation coupled with strong programming, documentation and communications skills.
Must have experience implementing complex market or credit risk quantitative modelling for OTC derivatives using programming languages (such as Python and C++) as well as mathematical/statistical software packages.
Knowledge of derivatives pricing models (Black Scholes, Hull White), Monte Carlo simulation, and risk model back testing experience is also a must.
Nice to have:
The candidate is preferred (a plus) to have experience in credit risk modelling and is familiar with credit risk concepts such as PFE (Potential Future Exposure), CSA, MPOR, collaterals IM and VM, and Monte Carlo simulation of long-time horizons.

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