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Data Scientist Risk Jobs (NOW HIRING)

Unchain Data

NY · On-site

We're looking for a Data Scientist who'll effectively assess and manage risk by developing policies, methodologies, models, and systems for risk quantification, reporting, and monitoring. What You'll ...

Gusto, Inc.

Data Scientist, Risk

San Francisco, CA · On-site +1

$186K - $230K/yr

As a Data Scientist supporting Risk, you will play a crucial role in leveraging experimentation, statistical inference, and causal analysis to drive strategic decision making that contributes to the ...

Gusto, Inc.

Data Scientist, Risk

San Francisco, CA · On-site

$186K - $230K/yr

As a Data Scientist supporting Risk, you will play a crucial role in leveraging experimentation, statistical inference, and causal analysis to drive strategic decision making that contributes to the ...

Imprint

Data Scientist, Risk

New York, NY · On-site +1

$170K - $200K/yr

As a Data Scientist, Risk, you will own the modeling powering Imprint's top-of-funnel credit decisioning-from application intake through approval-across every acquisition channel: direct affiliates ...

Mudflapinc

Senior Data Scientist, Risk

Palo Alto, CA · On-site

$185K - $225K/yr

Senior Data Scientist, Risk Location: Palo Alto, CA Employment Type: Full time Location Type: Hybrid Department: Data Compensation: $185K - $225K Mudflap serves the $800B trucking industry, the ...

Mudflap

Senior Data Scientist, Risk

Palo Alto, CA · On-site

$220K - $245K/yr

As a Senior Data Scientist, Risk , you will develop the models, insights, and strategies that help us identify, assess, and mitigate credit and fraud risk across our platform. You'll lead the ...

Mudflap

Senior Data Scientist, Risk

Palo Alto, CA · On-site

$185K - $225K/yr

We're looking for a versatile Senior Data Scientist, Risk to join our high-impact team. In this role, you will develop the models, insights, and strategies that help us identify, assess, and mitigate ...

Turo

Senior Data Scientist, Risk

San Francisco, CA · Hybrid

$156K - $195K/yr

Operate at the nexus of Data Science and Risk strategy. You will work cross-functionally with Data Analytics, Trust & Safety, and Product teams to develop frameworks driving key product and modeling ...

Turo

Senior Data Scientist, Risk

San Francisco, CA · On-site

$156K - $195K/yr

Operate at the nexus of Data Science and Risk strategy. You will work cross-functionally with Data Analytics, Trust & Safety, and Product teams to develop frameworks driving key product and modeling ...

Turo Inc.

Senior Data Scientist, Risk

San Francisco, CA · On-site

$156K - $195K/yr

Operate at the nexus of Data Science and Risk strategy. * You will work cross-functionally with Data Analytics, Trust & Safety, and Product teams to develop frameworks driving key product and ...

OKX

Sr Data Scientist, Risk Strategy

San Jose, CA · Hybrid

$223K - $268K/yr

The Sr Data Scientist, Risk will offer a strategic perspective, deep analytical and modeling capabilities, and a collaborative working style. The right candidate will have strong intellectual ...

OKX

Sr Data Scientist, Risk Strategy

San Jose, CA · On-site

$223K - $268K/yr

The Sr Data Scientist, Risk will offer a strategic perspective, deep analytical and modeling capabilities, and a collaborative working style. The right candidate will have strong intellectual ...

Jobtailor

Data Scientist, Fraud Risk

California, MO · On-site

Data Science * Risk Analytics * Model Validation * Feature Engineering * Machine Learning * Fraud Detection * KYC Controls * AML Compliance * Data Transformation * Decision System Evaluation Soft ...

Flexcar LLC

Risk Data Scientist

Boston, MA · On-site

Risk Data Scientist Location: Downtown B oston - Preferred Onsite-CA/GA/TX -Optional Onsite hub locations Employment Type: Exempt Full Time Compensation: $112,000 - $155,000 + Full Benefit Package ...

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How much do data scientist risk jobs pay per year?

As of Sep 12, 2026, the average yearly pay for data scientist risk in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is a data scientist risk?

A Data Scientist Risk job involves using data analysis, machine learning, and statistical modeling to assess and mitigate financial, credit, or operational risks. These professionals work with large datasets to identify patterns, detect anomalies, and build predictive models that help organizations make informed decisions. They collaborate with risk management teams and stakeholders to develop strategies for minimizing potential losses while ensuring regulatory compliance. Strong analytical skills, proficiency in programming languages like Python or R, and knowledge of risk modeling techniques are essential for this role.

What types of projects or problems does a data scientist risk typically work on?

Data Scientist Risk professionals typically work on projects involving risk assessment, fraud detection, credit scoring, market risk analysis, and regulatory compliance. Their day-to-day responsibilities often include analyzing large datasets to identify patterns, building predictive models, and presenting insights to risk managers or executives to support risk mitigation strategies. You'll often collaborate with cross-functional teams including finance, IT, and compliance to develop innovative risk solutions and improve organizational decision-making. The work environment is dynamic and intellectually challenging, offering opportunities to continuously learn and make an impact in critical business areas.

What are the key skills and qualifications needed to thrive as a data scientist risk?

To excel as a Data Scientist Risk, you need strong analytical skills, advanced knowledge of statistics, programming (typically in Python or R), and a relevant degree such as mathematics, finance, or data science. Familiarity with machine learning libraries, data visualization tools, and risk modeling software like SAS or SQL is commonly required, and certifications such as FRM or CFA are advantageous. Excellent problem-solving, critical thinking, and clear communication abilities are vital for interpreting complex data and presenting actionable insights to stakeholders. These competencies are crucial for accurately assessing risk, supporting decision-making, and ensuring regulatory compliance in fast-paced business environments.

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Data Scientist Risk jobs near you
Infographic showing various Data Scientist Risk job openings in the United States as of September 2026, with employment types broken down into 100% Full Time. Highlights an 87% In-person, and 13% Hybrid job distribution, with an average salary of $122,738 per year, or $59 per hour.

Data Scientist (Risk)

NY • On-site

Unchain Data
See more jobs at Unchain Dataexternal

Other

Re-posted 7 days ago

Job description

About Revolut

People deserve more from their money. More visibility, more control, and more freedom. Since 2015, Revolut has been on a mission to deliver just that. Our powerhouse of products — including spending, saving, investing, exchanging, travelling, and more — help our 75+ million customers get more from their money every day.

As we continue our lightning-fast growth, 2 things are essential to our success: our people and our culture. In recognition of our outstanding employee experience, we've been certified as a Great Place to Work. We have 13,000+ people working around the world, from our offices and remotely, to help us achieve our mission. We're looking for more brilliant people who love building great products, redefining success, and turning the complexity of a chaotic world into the simplicity of a beautiful solution.

About The Role

Our Data Science team solves complex problems with smart, practical solutions. Data Scientists and Analysts work directly with product teams to uncover insights, guide decisions, and improve how customers experience Revolut. They do this by delivering smart, scalable solutions that move the business forward.

We're looking for a Data Scientist who’ll effectively assess and manage risk by developing policies, methodologies, models, and systems for risk quantification, reporting, and monitoring.

What You’ll Be Doing
  • Developing and maintaining methodologies and policies for liquidity and market derivative modelling
  • Delivering real impact to the product through rigorous data-driven solutions
  • Building, enhancing, and maintaining the core risk engine, including margin models, leverage frameworks, and liquidation logic
  • Developing and calibrating risk models across isolated/cross margin, partial/full liquidation, bankruptcy pricing, and future portfolio margining capabilities
  • Collaborating with Engineering to deploy risk methodologies into production systems while iteratively improving models based on market conditions
  • Automating advanced analytic workflows, including P&L attribution, daily risk reporting, short-term investment performance, and cash flow analysis
  • Preparing documentation for compliance, and presenting risk insights, exposures, and recommendations to senior leadership
Requirements
  • A degree in mathematics, statistics, financial engineering, machine learning, or computer science
  • 3+ years of experience in machine learning, financial engineering, or similar roles within liquidity or market derivatives
  • Knowledge of margin trading mechanics, derivatives pricing models, and liquidation/liquidity risk management
  • Expertise in building and validating risk and margin models (VaR, Expected Shortfall, SPAN, CCP-style IM/VM, stress tests, scenario simulations)
  • Proficiency in quantitative modelling and time-series methods (GARCH, ARIMA, stochastic calculus), with advanced Python and SQL skills for large-scale data analysis
  • Familiarity with high-frequency datasets, and the ability to work well in fast-paced risk environments
Nice to Have
  • Experience at a major financial institution, asset manager, or liquidity provider, or within a treasury or risk department (FTP, ALM, liquidity, IRRB, etc.)
  • Exposure to market-making workflows and risks (inventory management, P&L drivers, spread optimisation, and internalisation strategies)
  • Familiarity with regulatory and institutional risk frameworks (Basel III/IV, FRTB, SA-CCR, CCP margin methodologies)
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