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At Home Data Scientist Risk Jobs (NOW HIRING)

Imprint

Data Scientist, Risk

New York, NY · On-site +1

$170K - $200K/yr

Role Summary The Risk team at Imprint is responsible for making smarter, faster credit decisions ... As a Data Scientist, Risk, you will own the modeling powering Imprint's top-of-funnel credit ...

Binance.US

Senior Data Scientist, RIsk

Vancouver, WA · Remote

Learn more at www.binance.us. All roles supporting Binance.US are employed via BAM Management US ... Fully remote, cameras-on culture with work-from-home equipment reimbursements available to new ...

OKX

Sr Data Scientist, Risk Strategy

San Jose, CA · On-site

The Sr Data Scientist, Risk will leverage analytical and modeling skills to identify fraud patterns, collaborate with stakeholders, and develop machine learning models to enhance fraud detection ...

OKX

Sr Data Scientist, Risk Strategy

San Jose, CA · Hybrid

$223K - $268K/yr

Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute ... The Sr Data Scientist, Risk will offer a strategic perspective, deep analytical and modeling ...

Makpar

Senior Data Scientist / Risk Modeling Analyst

$88K - $111K/yr

Learn more about our employer brand at makpar.com/careers. The Senior Data Scientist will support the Safeguards risk-based review selection process. This role will maintain and enhance risk models ...

Flexcar

Risk Data Scientist

Boston, MA · On-site

Risk Data Scientist Location: Downtown Boston, MA Employment Type: Exempt Full Time - 5 days in ... At Flexcar, our mission is to make car ownership flexible, affordable, and enjoyable for everyone.

Cotiviti

The Generative AI Scientist - Risk will apply knowledge and experience to real world problems and ... As a Data Scientist on this team, you will focus on three main project areas: Model Validation ...

TradeStation Group, Inc.

Principal Data Scientist

Are you ready to make yourself at home? What We Are Looking For: We're seeking a Principal Data ... Work with Compliance and Risk teams to build surveillance and monitoring systems that meet ...

Analygence

Data Scientist

Arlington, VA · On-site

... at enterprise scale. This individual works independently on high-visibility and mission-critical ... Design, build, and sustain analytical models that support COA analysis, risk prioritization ...

TradeStation

Principal Data Scientist

Are you ready to make yourself at home? What We Are Looking For: We're seeking a Principal Data ... Work with Compliance and Risk teams to build surveillance and monitoring systems that meet ...

Elder Research

Data Scientist

Arlington, VA · On-site

... risk identification across large, complex tax and financial data environments. You will work ... Willingness to travel and work on-site at client locations as required by project needs Preferred ...

Analygence

Data Scientist

Arlington, VA

Design, build, and sustain analytical models that support COA analysis, risk prioritization ... Aggregate, normalize, prioritize, and analyze Mission Assurance risks and dependencies at ...

Elder Research

Data Scientist

Arlington, VA

... risk identification across large, complex tax and financial data environments. You will work ... Willingness to travel and work on-site at client locations as required by project needs Preferred ...

Maymont Homes

Data Scientist

Charleston, SC · On-site

... truly at home. **This position is onsite at 997 Morrison Dr, Charleston SC** Primary ... The Data Scientist leverages advanced analytics, statistical modeling, machine learning, and AI to ...

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All JobsAt Home Data Scientist Risk Jobs

At Home Data Scientist Risk information

See salary details

$37.5K

$122.7K

$196.5K

How much do at home data scientist risk jobs pay per year?

As of Jul 31, 2026, the average yearly pay for at home 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 the difference between At Home Data Scientist Risk vs At Home Data Analyst Risk?

AspectAt Home Data Scientist RiskAt Home Data Analyst Risk
Required CredentialsTypically requires a master's or Ph.D. in data science, statistics, or related fieldsUsually requires a bachelor's degree in data analysis, statistics, or related areas
Work EnvironmentRemote, often involves complex modeling and predictive analyticsRemote, focuses on data interpretation and reporting
Employer & Industry UsageUsed in tech, finance, healthcare for advanced analyticsCommon in retail, marketing, and business sectors for reporting

The main difference between At Home Data Scientist Risk and At Home Data Analyst Risk lies in the complexity of tasks and required credentials. Data Scientists typically handle advanced modeling and require higher education, while Data Analysts focus on data reporting and analysis with more accessible qualifications. Both roles are remote and industry-specific, but Data Scientists often work on predictive analytics, whereas Data Analysts interpret existing data for decision-making.

More about At Home Data Scientist Risk jobs
What cities are hiring for At Home Data Scientist Risk jobs? Cities with the most At Home Data Scientist Risk job openings:
What are the most commonly searched types of Data Scientist Risk jobs? The most popular types of Data Scientist Risk jobs are:
What states have the most At Home Data Scientist Risk jobs? States with the most job openings for At Home Data Scientist Risk jobs include:
What job categories do people searching At Home Data Scientist Risk jobs look for? The top searched job categories for At Home Data Scientist Risk jobs are:
At Home Data Scientist Risk jobs near you
Infographic showing various At Home Data Scientist Risk job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 73% Full Time, 22% Part Time, and 4% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% 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 2 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.

Apply