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Senior Fraud Data Scientist Jobs (NOW HIRING)

Imprint

Data Scientist, Fraud Risk

New York, NY · On-site +1

$170K - $200K/yr

As a Data Scientist focused on Onboarding Fraud, you will own the modeling and analytics that power ... senior leadership and external partners Your Profile Required * 5 to 8+ years of experience in data ...

Betterment

Sr. Fraud Analyst

New York, NY · Hybrid

$135K - $160K/yr

As a Senior Fraud Analyst, you will be the analytical owner of our customer risk rating, KYC, and ... You will use data to shape how we detect, prevent, and respond to emerging fraud trends. You will ...

Betterment

Sr. Fraud Analyst

New York, NY · On-site

$135K - $160K/yr

As a Senior Fraud Analyst, you will be the analytical owner of our customer risk rating, KYC, and ... You will use data to shape how we detect, prevent, and respond to emerging fraud trends. You will ...

ALOIS LLC

Sr Fraud Analyst

San Jose, CA · On-site

$140K - $165K/yr

Analyze large-scale payment and fraud transaction data to identify trends, anomalies, and business opportunities. * Drive insights related to credit/debit card payments, fraud prevention ...

Manulife Financial

Senior Data Scientist

Boston, MA · On-site

We are seeking a highly skilled and motivated Senior Data Scientist - GenAI to join the Long Term ... Lead end to end development of fraud detection and risk analytics models, including probabilistic ...

Manulife Financial

We are seeking a highly skilled and motivated Senior Data Scientist - GenAI to join the Long Term ... Lead end to end development of fraud detection and risk analytics models, including probabilistic ...

New

GD Resources LLC

Data Scientist - Remote Role

2. Senior Data Scientist (1 Positions) Position Title - Senior Data Scientist Location: Remote ... The position directly supports audits, investigations, and fraud prevention initiatives by ...

ManTech

Senior Data Scientist

Arlington, VA · On-site +1

As a Data Scientist, you will support the Internal Revenue Service's mission to improve tax compliance, fraud detection, and risk identification across large, complex tax and financial data ...

Manulife

Senior Data Scientist

Boston, MA · Hybrid

We are seeking a highly skilled and motivated Senior Data Scientist - GenAI to join the Long Term ... Lead end to end development of fraud detection and risk analytics models, including probabilistic ...

Reddit

Senior Data Scientist, Ads Integrity

We are looking for a Senior Data Scientist to lead ads fraud detection and scaled enforcement within Safety. You will partner closely with Ads Product, Engineering, Machine Learning, Operations ...

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Senior Fraud Data Scientist information

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$41.5K

$142.5K

$201K

How much do senior fraud data scientist jobs pay per year?

As of Sep 12, 2026, the average yearly pay for senior fraud data scientist in the United States is $142,460.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,500.00 and $166,500.00 per year, depending on experience, location, and employer.

What does a senior fraud data scientist do?

A Senior Fraud Data Scientist is responsible for detecting and preventing fraudulent activities by analyzing large datasets and developing advanced models. They use statistical techniques, machine learning, and data mining to identify patterns and anomalies that may indicate fraud. Additionally, they collaborate with engineering, product, and compliance teams to implement fraud prevention strategies and improve existing systems. Their expertise helps organizations minimize financial losses, meet regulatory requirements, and protect customers from fraud.

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

To thrive as a Senior Fraud Data Scientist, you need advanced expertise in statistical analysis, machine learning, and data mining, typically supported by a degree in computer science, statistics, or a related field. Familiarity with programming languages such as Python or R, experience with big data platforms like Spark or Hadoop, and knowledge of fraud detection systems are crucial. Strong problem-solving, critical thinking, and communication skills help you effectively interpret data patterns and explain findings to stakeholders. These capabilities are essential for developing robust fraud prevention models and ensuring business integrity.

How does a senior fraud data scientist typically collaborate with cross-functional teams to enhance fraud detection systems?

A Senior Fraud Data Scientist often works closely with engineering, product, and risk management teams to develop and refine fraud detection models. They communicate complex analytical findings to stakeholders, help prioritize features, and ensure that models are both accurate and scalable. Regular collaboration involves sharing insights from data analysis, advising on data collection strategies, and integrating machine learning solutions into production systems. This cross-functional teamwork is essential to address evolving fraud patterns and maintain robust protection for the organization.

What is the difference between Senior Fraud Data Scientist vs Fraud Data Scientist?

AspectSenior Fraud Data ScientistFraud Data Scientist
Required CredentialsAdvanced degree in Data Science, Statistics, or related field; experience with fraud detection modelsSimilar educational background; entry to mid-level experience in fraud analytics
Work EnvironmentTypically in larger financial or e-commerce companies; involves leadership and mentorship rolesOften in similar industries; focuses on data analysis and model development
Employer & Industry UsageUsed in banking, finance, e-commerce, and insurance sectors for fraud preventionCommonly employed in the same sectors, often as part of fraud or risk teams

The main difference between a Senior Fraud Data Scientist and a Fraud Data Scientist lies in experience level, leadership responsibilities, and scope of work. Senior Fraud Data Scientists usually have more advanced skills, lead projects, and mentor junior staff, whereas Fraud Data Scientists focus on developing and implementing fraud detection models at an operational level.

What are the most commonly searched types of Fraud Data Scientist jobs?

The most popular types of Fraud Data Scientist jobs are:

What states have the most Senior Fraud Data Scientist jobs?

States with the most job openings for Senior Fraud Data Scientist jobs include:

What are popular job titles related to Senior Fraud Data Scientist jobs?

For Senior Fraud Data Scientist jobs, the most frequently searched job titles are:

Infographic showing various Senior Fraud Data Scientist job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $142,460 per year, or $68.5 per hour.

Data Scientist, Fraud Risk

New York, NY • On-site, Remote

Imprint
Printing and Printing Services • 501 - 1,000 employees
Learn more about Imprintexternal

$170K - $200K/yr

Full-time

Medical, PTO

Posted 7 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.
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.
As a Data Scientist focused on Onboarding Fraud, you will own the modeling and analytics that power fraud and identity decisions from application submission through account opening. Your goal will be to stop identity theft, synthetic identity, first-party fraud, and other forms of application abuse while minimizing false positives, unnecessary verification, and friction for legitimate applicants.
You will partner closely with Fraud Strategy and Operations, Product, Engineering, Compliance, and Credit Strategy to improve onboarding fraud and KYC decisioning. You will build models, evaluate third-party fraud and identity vendors, test new scores and attributes, design experiments, and translate emerging fraud patterns into scalable policy changes. You will also build monitoring and AI-powered analytical workflows that detect shifts, diagnose root causes, and help the team respond quickly as fraud tactics evolve.
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

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