Level

Socure

Staff Data Scientist - Fraud & Risk

Socure is hiring a Staff Data Scientist - Fraud & Risk in San Francisco, United States. It pays $180k-$210k a year and Level rates it ; you can apply on Socure.

Level's read on this job

  • On Level's scale, this data scientist role is Builds AI ●●●●: the job is building AI systems.
  • The listed pay starts 8% above the typical data scientist posting on Level.
  • The posting allows some remote work.
  • Tools and skills the posting cites include LangChain, LangGraph and PyTorch.
  • Level lists 82 other open roles at Socure.

AI in this role

langchainlanggraphpytorchtensorflowscikit-learn
ai-evaluation

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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How we rate this

Staff Data Scientist - Fraud & Risk at Socure rates 98 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI EvaluationLangChainLangGraphPyTorchTensorFlowscikit-learn

Also common in data scientist jobs at this level

Pay

This job starts at
$180k
Typical data scientist job
$166k

This posting starts 8% above the typical data scientist job. See data scientist jobs

Questions you could be asked

  1. How do you decide that one model's output is better than another's for a given task?
  2. Walk me through how you've used LangChain in your day-to-day work.
  3. What are the limits of LangGraph that you've run into, and how did you work around them?
  4. What's a project where you used PyTorch hands-on?
  5. Walk me through how you've used TensorFlow in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: AI Evaluation, LangChain, LangGraph, PyTorch, and TensorFlow. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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