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Remote Data Scientist Risk Jobs (NOW HIRING)

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 ...

Found

Senior Data Scientist, Risk

New York, NY · On-site +1

$163K - $225K/yr

As a Risk Data Scientist at Found, you will be a key player in our Risk team, responsible for ... For team members who work outside those cities, Found also supports fully remote working.

WEX

Fraud / Credit Data Scientist, Risk Solutions

The Risk Solutions Team employs data science methodologies (machine learning and statistical frameworks), a wide suite of data types, and modern technologies to develop solutions to inform decision ...

eNett

Fraud / Credit Data Scientist, Risk Solutions

The Risk Solutions Team employs data science methodologies (machine learning and statistical frameworks), a wide suite of data types, and modern technologies to develop solutions to inform decision ...

kgs

Data Scientist (Remote)

Nashville, TN · Remote

... remote environment to deliver data science solutions that drive measurable improvements in IT Call ... risk prediction, agent performance modeling, and customer satisfaction analytics. * Collaborate ...

Koniag, Inc.

Data Scientist (Remote)

Nashville, TN · On-site +1

... remote environment to deliver data science solutions that drive measurable improvements in IT Call ... risk prediction, agent performance modeling, and customer satisfaction analytics. * Collaborate ...

kgs

Data Scientist (Remote)

Nashville, TN · Remote

... remote environment to deliver data science solutions that drive measurable improvements in IT Call ... risk prediction, agent performance modeling, and customer satisfaction analytics. * Collaborate ...

MM International

Data Scientist

New York, NY · Remote

Remote Duration 4-6 months The RBQM Data Scientist supports central monitoring and risk-based quality management (RBQM) for clinical trials. This role focuses on implementing and running pre-defined ...

Prosper

Data Scientist, Credit Risk Analytics

$129K - $179K/yr

Your role in our mission Prosper is seeking a Data Scientist under the Credit Risk Analytics ... Whether you are working from our San Francisco or Phoenix offices or joining us as a fully remote ...

Booz Allen Hamilton, Inc.

Data Scientist

Alexandria, VA · On-site +1

Remote Work: No Job Number: R0241573 Location: Alexandria,VA,US Share job via: Share Data Scientist ... risk, and develop courses of action. Employ expert judgment, adaptable methodologies, repeatable ...

Addison Group

Sr. Data Scientist

Chicago, IL · Remote

$85 - $100/hr

Remote Contract Pay: $85/hr - $100/hr The Senior Data Scientist will design and implement AI ... Translate risk management business requirements into well-defined data science solutions, includin ...

1 point system

Senior Data Scientist

Chicago, IL · Remote

Requirement - Senior Data Scientist Location- Chicago, IL-Remote Contract W2 Updated JD PURPOSE ... This role will help risk management teams identify high-risk incidents earlier, classify claims by ...

Match Point Solutions

Data Scientist

Pleasanton, CA · Remote

$75 - $80/hr

Remote Rate: $75-$80/hr on W2 Key points: Developing computer vision models that improve ... Creating wildfire risk models that are used by regulators and the utility to prioritize asset ...

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How much do remote data scientist risk jobs pay per year?

As of Aug 22, 2026, the average yearly pay for remote 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.
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Remote Data Scientist Risk jobs near you
Infographic showing various Remote Data Scientist Risk job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Data Scientist, Risk

Imprint

New York, NY • On-site, Remote

$170K - $200K/yr

Full-time

Medical, PTO

Re-posted 23 days ago

Job description

Who We Are
Imprint helps the world's best brands grow the lifetime value of their customers. We started with co-branded credit cards and rebuilt them to be smarter, more rewarding, and brand-first. We partner with companies like Crate & Barrel, Rakuten, Booking.com, H-E-B, Fetch, and Shell to launch modern credit programs that deepen loyalty, unlock savings, and drive growth. But the card is just the beginning. We combine advanced payments infrastructure, intelligent underwriting, and deep customer data to create delightful and personalized experiences for members as well as efficient and profitable relationships for our brand partners. Our robust technology and world-class operations allow us and our brand partners to offer powerful financial products without becoming a bank.
In the U.S., co-branded cards alone account for over $300 billion in annual spend, and most still run on decades-old legacy bank systems. Imprint is the modern alternative: flexible, embeddable, and built for how people actually pay today. Backed by Kleiner Perkins, Thrive Capital, Ribbit, and Khosla Ventures, we're building a world-class team to redefine how people pay and how brands grow. If you want to move fast, solve hard problems, and own real outcomes, we want to meet you.
Role Summary
The Risk team at Imprint is responsible for making smarter, faster credit decisions that balance growth with responsible risk management. The team builds the models, policies, and analytical systems that power underwriting, fraud detection, and portfolio optimization across all of Imprint's credit programs.
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 (Credit Karma, NerdWallet), invitation-to-apply emails, direct mail, paid social, instant prescreens, and on-site applications. Your primary focus will be improving approval rates while maintaining credit quality: building better underwriting models, designing policy experiments, and uncovering segments where we can safely expand access to credit.
This role sits at the intersection of credit and acquisition strategy. You will partner directly with Credit Strategy, Product, Engineering, and Marketing to build targeting models for new channels, evaluate channel-level credit performance, and connect acquisition volume to downstream economics-approval rates, vintage loss forecasts, LTV, CAC, and contribution profit. Increasingly, that means building not just analyses but AI-powered systems that can autonomously monitor approval rate, channel performance, diagnose shifts, and recommend policy adjustments.
The Opportunity
  • Own and improve the full top-of-funnel credit decisioning pipeline: application scoring, policy rules, decline waterfalls, and approval rate optimization across direct affiliates, invitation-to-apply, direct mail, paid social, instant prescreens, and on-site applications
  • Build and iterate on underwriting, targeting, and segmentation models that expand safe approvals and improve channel-level acquisition quality
  • Design and analyze A/B tests and champion/challenger experiments on credit policies, establishing a test-and-learn cadence with structured readouts on both acquisition and credit performance
  • Build channel-level performance models that connect application volume to downstream economics: approval rates, expected losses, LTV, CAC, and contribution profit
  • Design and build agentic workflows and AI-powered monitoring systems that autonomously detect approval rate anomalies, diagnose score drift and population mix changes, and recommend policy adjustments
  • Partner directly with Credit Strategy, Product, Engineering, and Marketing to develop targeting criteria and risk frameworks for new and emerging acquisition channels
  • Build segmentation frameworks to identify underserved populations where credit access can be responsibly expanded

Your Profile
Required
  • 5 to 8+ years of experience in data science, risk analytics, or a related quantitative field, ideally at a high-growth startup or fintech company
  • Strong Python and SQL skills, with the ability to build models, transform raw data, and create custom datasets from complex financial data
  • Experience building credit risk or targeting models (scorecards, underwriting models, segmentation) or similar predictive modeling in a regulated environment
  • Deep understanding of statistical inference, experimentation design, and causal analysis, with the ability to disentangle policy impact from population shifts and channel mix changes
  • Comfort with AI tools and AI-native workflows; you actively use tools like Claude, Copilot, or similar to accelerate your work and are excited to build AI-powered analytical systems
  • Full-stack problem-solving orientation: you dive into messy data, trace a decline to its root cause, and question assumptions in pursuit of a better answer
  • Ability to present complex findings clearly to technical and non-technical audiences, including senior leadership and external partner stakeholders
  • Comfort owning projects end-to-end in a fast-moving startup environment with limited scaffolding, collaborating cross-functionally with Policy, Strategy, Product, and Engineering

Nice to Have
  • Experience with credit card underwriting, lending, or consumer credit products
  • Familiarity with credit bureau data (Vantage, FICO, tradeline attributes) and alternative data sources
  • Experience building or scaling experimentation infrastructure for credit policy testing
  • Exposure to fraud detection, KYC/IDV workflows, or application fraud models
  • Understanding of acquisition channel economics and experience partnering with marketing or credit strategy teams on targeting and LTV modeling

We don't expect every candidate to check every box. If this role excites you and you bring strong fundamentals, we encourage you to apply.
Stack
Python and SQL for modeling and analysis. Snowflake for data warehousing. AWS infrastructure. Dashboarding and monitoring tools for production systems.
Learn More
Learn more about how we build at Imprint on our engineering blog: https://medium.com/imprint-eng
Perks & Benefits
  • Competitive compensation and equity packages
  • Leading configured work computers of your choice
  • Flexible paid time off
  • Fully covered, high-quality healthcare, including fully covered dependent coverage
  • Additional health coverage includes access to One Medical and the option to enroll in an FSA
  • 20 weeks of paid parental leave for the primary caregiver and 8 weeks for all new parents
  • Access to industry-leading technology across all of our business units, stemming from our philosophy that we should invest in resources for our team that foster innovation, optimization, and productivity

Imprint is committed to a diverse and inclusive workplace. Imprint is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. Imprint welcomes talented individuals from all backgrounds who want to build the future of payments and rewards. If you are passionate about FinTech and eager to grow, let's move the world forward, together.

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