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Staff Data Scientist - Fraud & Risk

Hub - New York · Hub - San Francisco · New York, United States

Pay
Pay not listedSimilar roles state $118K–$193K
Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
AI and Data — team source
Department: AI and Data
From the employer’s posting

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Sponsorship
Visa sponsorship not confirmed — sponsorship source
Will you now or in the future require sponsorship for employment visa status in this country? Mark Yes: Candidates on H1, L1, O1, visas that will require sponsorship now or in the future.
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Apply at Socure

What you’ll work on

Full posting
  • Design and build deep learning models (transformers, CNNs/RNNs, graph learning) for fraud and risk

  • Lead models end to end: feature engineering, training, deployment and monitoring

  • Work with tabular, text, point cloud and image data

  • Mentor peers and junior data scientists

  • Present findings and recommendations to technical and executive stakeholders

From the employer’s posting
Design, develop, and implement advanced deep learning models, including transformers, CNNs/RNNs, and graph learning algorithms
Lead the end-to-end machine learning lifecycle: data exploration, feature engineering, model training, evaluation, deployment, and monitoring in production environments
Build and optimize models using a variety of input data types, including tabular data, natural language, point clouds, and images
Mentor and share knowledge with peers and junior data scientists
Present findings and recommendations to technical and executive stakeholders with clarity and influence
Education & alternatives
Job Requirements - 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.

Tools in this posting

  • Python
  • SQL
  • PyTorch
  • scikit-learn
  • TensorFlow
Source — Tool mentions in context
- 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.

Posting record

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Live
First seen by us
Sep 15, 2026 · 45 days ago
Recorded sightings
106
Last seen by us
Oct 30, 2026

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Job description

View original posting ↗

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.

Staff Data Scientist – Fraud & Risk

 

Job Overview

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.

 
 

Job Responsibilities

  • 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.

 
 

Job Requirements

  • 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.

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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New York, United States

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