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Socure

Digital identity verification and fraud prevention

Data Scientist 2 - Fraud & Risk

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeHybrid

About the Job

Requirements

  • A bachelor's degree with substantial related experience, a master's degree with relevant experience, or equivalent work background in Computer Science, Statistics, Mathematics, Engineering, or a related field is required.
  • Two to four years of hands-on experience developing and deploying deep learning models, such as transformers, CNNs, and LSTMs, is required.
  • Experience working with diverse data modalities, such as tabular data, text or language, point clouds, and images, is required.
  • Proficiency in Python and major machine learning libraries or frameworks such as PyTorch, TensorFlow, and scikit-learn is required.
  • A foundational understanding of machine learning algorithms, model evaluation techniques, and data pipeline development is required.
  • Experience with model deployment and monitoring in production environments is required.
  • Experience with real-time model inferencing is a plus.
  • Strong problem-solving skills and the ability to work independently on straightforward tasks and contribute effectively to project objectives are required.
  • The ability to collaborate in a diverse, cross-functional team environment is required.
  • Excellent written and verbal communication skills are required.

Responsibilities

  • Design, develop, and implement advanced deep learning models, including transformers, CNNs, and LSTMs, to address fraud and risk challenges.
  • Build and optimize models using tabular data, natural language, point clouds, and images.
  • Take ownership of assigned tasks and execute technical and functional activities to support project goals with minimal supervision.
  • Participate in all stages of the machine learning lifecycle, including data exploration, feature engineering, model training, evaluation, and deployment.
  • Collaborate across teams, sharing knowledge and learning from diverse perspectives to drive results.
  • Make routine technical decisions and contribute to functional objectives through productive and proactive engagement.
  • Stay current with advancements in artificial intelligence and machine learning, applying innovative approaches to real-world problems.
  • Communicate results and insights clearly to technical and non-technical audiences.

Desired Qualifications

  • Experience with large language models and Agentic AI frameworks or infrastructure such as LangChain, LangGraph, or Ray is a plus.
  • Experience in fraud prevention, risk modeling, or identity verification is a plus.

About the Company

Socure

Digital identity verification and fraud prevention

Socure provides digital identity verification and fraud prevention services for financial institutions through a subscription-based platform. It uses machine learning and advanced algorithms to analyze small amounts of customer data to predict fraud risk. A flagship feature, the Sigma Fraud Score, compares transactions against a proprietary database of known fraudulent users and traits to detect suspicious activity. Additional tools like Device Risk verify session authenticity by gathering device and browser signals, supporting seamless and secure customer experiences. Socure differentiates itself with a robust, data-driven fraud scoring system, a suite of identity verification and compliance tools, and continuous platform updates delivered as a service. Its goal is to help banks and other lenders verify customers quickly and accurately while reducing fraud and ensuring regulatory compliance (e.g., Customer Identification Programs under the Patriot Act).

Company size
501-1,000
Company stage
Series F
Total funding
$900.1M
Headquarters
Incline Village-Crystal Bay, Nevada
Founded
2012

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