Data Scientist, Fraud Risk

Imprint; San Francisco (CA); On-site; USD 170,000 - 200,000; Full time

Benefits offered by this job

Equity

Healthcare

PTO

Parental leave

One Medical access

FSA

Job summary

Imprint is seeking a senior data scientist focused on fraud risk to own onboarding decisioning across the full application journey, including identity verification, KYC controls, and policy rules. You will build, validate, deploy, and monitor models that detect identity theft, synthetic identity, and coordinated abuse, leveraging identity, device, behavioral, bureau, and consortium signals.

You will evaluate third-party fraud vendors, design robust experiments, and collaborate with Fraud

Qualifications

• 5 to 8+ years of experience in data science, risk analytics, or related quantitative field.
• Strong Python and SQL skills, with ability to build models and transform data.
• Experience building and evaluating predictive models for fraud, identity, KYC, AML, or adversarial classification.
• Strong understanding of supervised ML, model validation, backtesting, calibration, feature engineering, and production monitoring.
• Deep understanding of statistical inference and experiment design, including A/B tests and causal measurement.

Responsibilities

• Own and improve onboarding fraud decisioning across the full application journey, including identity verification and KYC controls.
• Build, validate, deploy, and monitor models that detect identity theft, synthetic identity, and coordinated fraud.
• Evaluate third-party fraud and identity vendors, testing scores, coverage, and cost.
• Design and analyze A/B tests, holdouts, and champion/challenger strategies to balance fraud losses and approvals.
• Investigate emerging fraud patterns and develop new features, rules, models, and review strategies.
• Build monitoring and AI-powered workflows to detect model drift and data quality issues.
• Partner with Fraud Operations, Product, Engineering, Compliance, and Credit Strategy to productionize changes.

Skills

Python

SQL

Data modeling

Fraud analytics

Model validation

A/B testing

Production monitoring

Communication

Tools

Snowflake

AWS

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.

The Team

The Risk team at Imprint builds the models, policies, and analytical systems that protect our credit card programs while delivering a fast and seamless member experience.

The Opportunity

• Own and improve Imprint's onboarding fraud decisioning across the full application journey, including identity verification, KYC controls, application fraud models, policy rules, decline and verification waterfalls, and manual-review strategies
• Build, validate, deploy, and monitor models that detect identity theft, synthetic identity, first-party fraud, and coordinated application abuse using identity, device, behavioral, application, bureau, network, and consortium signals
• Evaluate third-party fraud and identity vendors by testing scores and attributes, measuring incremental lift, overlap, coverage, stability, latency, and cost, and recommending when to add, replace, or retire signals
• Design and analyze A/B tests, shadow tests, holdouts, and champion/challenger strategies, balancing fraud losses and capture against approval rate, false positives, verification friction, and manual-review volume
• Investigate emerging fraud patterns and decision misses, combining application and post-booking outcomes with Fraud Operations feedback to develop new features, rules, models, and review strategies
• Build monitoring and AI-powered workflows that detect model drift, population shifts, vendor degradation, data-quality issues, and new attack patterns—and recommend adjustments for human review
• Partner with Fraud Operations, Product, Engineering, Compliance, and Credit Strategy to productionize changes, validate their impact, and communicate recommendations to senior leadership and external partners

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 and evaluating predictive models for fraud, identity, KYC, AML, credit risk, trust and safety, or another adversarial classification problem
• Strong understanding of supervised machine learning, model validation, backtesting, calibration, feature engineering, and production model monitoring
• Deep understanding of statistical inference and experiment design, including A/B tests, holdouts, champion/challenger tests, causal measurement, and tradeoff analysis
• Ability to evaluate decision systems—not just model performance—using metrics such as fraud capture, loss rate, false-positive rate, approval impact, verification friction, operational workload, and economic value
• Full-stack problem-solving orientation: you can trace a decision through raw inputs, vendor responses, model scores, policy rules, and downstream outcomes to find the root cause of a problem
• Comfort owning projects end-to-end, from problem definition and exploratory analysis through production implementation, monitoring, and business impact measurement
• Ability to communicate complex analytical findings and decision tradeoffs clearly to technical and non-technical audiences
• Comfort using AI tools to accelerate analysis, investigation, feature development, documentation, and monitoring—and excitement about building AI-powered risk systems

Nice to Have

• Experience with application or onboarding fraud, including identity theft, synthetic identity, first-party fraud, application manipulation, or fraud rings
• Familiarity with KYC, CIP, identity verification, document verification, device intelligence, behavioral signals, consortium data, credit bureau data, or alternative data sources
• Experience evaluating and integrating third-party fraud or identity vendors, including measuring incremental value relative to existing controls
• Experience with real-time scoring, decision engines, rules platforms, APIs, or production ML systems
• Experience partnering with fraud operations or investigations teams and converting case-review findings into scalable controls
• Familiarity with credit card underwriting, consumer lending, or regulated financial products
• Experience with graph, anomaly-detection, or weakly supervised methods for identifying coordinated or emerging fraud patterns

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.

Compensation Range: $170K - $200K