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Socure

The leading provider of digital identity verification and fraud solutions. Salesinfo@socure.com

Staff Data Scientist – Fraud & Risk

Data ScientistData ScientistOtherRemoteLeadTeam 501-1,000Since 2012H1B SponsorCompany SiteLinkedIn

Location

United States

Posted

131 days ago

Salary

$140K - $210K / year

Seniority

Lead

Postgraduate Degree8 yrs expEnglishPythonPyTorchRayscikit-learnSQLTensorFlow

Job Description

Staff Data Scientist – Fraud & Risk

Socure

• 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.

Benefits

  • Offers Equity
  • Offers Bonus

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