Staff Data Scientist - Fraud & Risk
Company websitesocure.com (Socure, opens in new tab)
Base salary $191K to $230K
Employer-published annual base salary, USD. Advertised base range in United States
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationUnited States
- WorkplaceHybrid
- Status at last checkSource accepting applications when checked
- Last checked (3 h ago) · observed since
All 4 locations
- Hybrid - San Francisco, CA
- Hybrid - New York, NY
- Hybrid - Miami, FL
- Hub - Seattle
About this job
Why Socure?
Socure is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day.
We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won’t be your place. If you want to help build the future of identity with a team that holds a high bar for itself — keep reading.
About the Role
We are seeking a skilled and motivated Staff Data Scientist to join our Fraud & Risk Data Science team. As an advanced-level individual contributor, you will design, build, and optimize advanced DS/ML models that power our core fraud detection and risk management solutions. You will lead technical initiatives, mentor peers, and drive functional productivity and project success. You will work hands-on with advanced deep learning models, driving delivery of impactful solutions for fraud detection, risk management, and identity verification. This role requires deep technical expertise, strategic ownership, and a commitment to Socure’s leadership principles, including continuous learning, effective communication, and accountability.
What You'll Do
Design, develop, and implement advanced deep learning models, including transformers, CNNs/RNNs, and graph learning algorithms, to address complex fraud and risk challenges.
Build and optimize models using a variety of input data types, including tabular data, natural language, point clouds, and images.
Lead the end-to-end machine learning lifecycle: data exploration, feature engineering, model training, evaluation, deployment, and monitoring in production environments.
Take ownership of project outcomes, data quality, and delivery timelines; proactively escalate issues and work collaboratively to resolve challenges.
Mentor and share knowledge with peers and junior data scientists, fostering a culture of experimentation, rapid iteration, and continuous learning.
Collaborate cross-functionally with Product, Engineering, and Risk teams to define data requirements and drive insights that guide strategic decisions.
Conduct in-depth research to explore new data sources and develop novel algorithms that advance the state of the art in fraud detection.
Present findings and recommendations to technical and executive stakeholders with clarity and influence.
Stay current with advancements in AI and machine learning, applying innovative approaches to real-world problems.
Model Socure’s embedded leadership competencies: continuous learning, effective communication, accountability, team development, decision making, and managing change.
What You Bring
Master’s or PhD in Computer Science, Statistics, Applied Mathematics, Data Science, or a related field; or equivalent professional experience.
8+ years of experience in data science, machine learning, or related fields, ideally in a high-growth tech or fintech environment.
Experience in fraud prevention, risk modeling, or identity verification.
Years of hands-on experience developing and deploying deep learning models (such as transformers, CNNs/RNNs, and graph learning).
Experience working with diverse data modalities, such as tabular data, text/language, point clouds, and images.
Strong proficiency in Python, SQL, and major ML libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
Deep understanding of machine learning algorithms, model evaluation techniques, and data pipeline development.
Experience with model deployment and monitoring in production environments (specific experience with real-time model inferencing is a plus)
Experience with LLMs and Agentic AI framework/infrastructure (e.g., LangChain/LangGraph/Ray) is a plus.
Demonstrated ability to proactively deliver complex outcomes, mentor others, and influence cross-functional decisions.
Excellent communication skills with the ability to translate complex data problems into actionable business insights for both technical and non-technical audiences.
Commitment to continuous learning, professional integrity, and high standards of business ethics.
Please note: we are unable to provide sponsorship now, or in the future.
Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly.
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Source: Socure on Ashby · View original posting (opens in new tab)
Pay in context
This role's base floor ($191,000) is above 70% of the 4,591 Data & ML roles nationwide listed on this site; 9 others list the same floor. Their median floor is $165,000; the middle half runs from $135,000 to $198,000.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 7, 2026.
This listingStaff Data Scientist - Fraud & Risk$191K to $230K
Staff Data Scientist - Fraud & Risk$191K to $230K
Staff Data Scientist, Watchlist$191K to $230K
Senior Software Engineer - Backend (DocV)$180K to $200K
Senior Frontend Engineer$180K to $210K
Senior Backend Engineer$180K to $210K
Senior AI Engineer$200K to $230K
Chart as a table
| Role | Published base |
|---|---|
| Staff Data Scientist - Fraud & Risk (this listing) | $191K - $230K |
| Staff Data Scientist - Fraud & Risk | $191K - $230K |
| Staff Data Scientist, Watchlist | $191K - $230K |
| Senior Software Engineer - Backend (DocV) | $180K - $200K |
| Senior Frontend Engineer | $180K - $210K |
| Senior Backend Engineer | $180K - $210K |
| Senior AI Engineer | $200K - $230K |
Observed changes
- Began meeting the published-salary criteria
- First observed on the employer's board
- Observed since
- Employer-stated posting date
- 2026-02-04
Where this pay comes from
Location as the employer wrote it: Multiple locations (4)
USD 191,000 – 230,000 · 1 YEAR · Salary
- Method
- Structured pay field published by the employer
- Checked
- Rule set
- us-base-v2
The employer's job board publishes this pay as a dedicated data field. We read the field directly; no interpretation was needed.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
