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Data Scientist (Fraud & Risk)

Socure

Skills

Required

  • deep learning
  • machine learning algorithms
  • model evaluation techniques
  • data pipeline development
  • Python
  • PyTorch
  • TensorFlow
  • scikit-learn

Preferred

  • LLMs
  • Agentic AI framework/infrastructure
  • LangChain / LangGraph / Ray
  • model deployment
  • monitoring in production environments
  • real-time model inferencing
  • fraud prevention / risk modeling / identity verification
  • evaluation
  • machine learning lifecycle
  • data exploration

Join our Fraud & Risk Data Science team as a Data Scientist II. In this role, you will design, develop, and implement advanced deep learning models to address complex fraud and risk challenges. You will have autonomy in your day-to-day work and play an important role in driving functional productivity and project success. This position offers the opportunity to contribute to diverse projects and collaborate within a supportive, high-performing team.

Responsibilities

  • Design, develop, and implement advanced deep learning models to address complex fraud and risk challenges.
  • Participate in all stages of the machine learning lifecycle, including data exploration, feature engineering, model training, evaluation, and deployment.

Requirements

  • Collaborate effectively across teams, sharing knowledge and learning from diverse perspectives to drive results.
  • Demonstrated ability to collaborate in a diverse, cross-functional team environment
  • Bachelor’s degree with substantial related experience, Master’s degree with relevant experience, or equivalent work background in Computer Science, Statistics, Mathematics, Engineering, or a related field

Excellent written and verbal communication skills

  • Foundational understanding of machine learning algorithms, model evaluation techniques, and data pipeline development
  • Proficiency in Python and major ML libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
  • Strong problem-solving skills, with the ability to work independently on straightforward tasks and contribute effectively to project objectives
  • 2-4 years of hands-on experience developing and deploying deep learning models (such as transformers, CNNs, and LSTMs)
  • Experience working with diverse data modalities, such as tabular data, text/language, point clouds, and images

Preferred

  • Experience with LLMs and Agentic AI framework/infrastructure (e.g., LangChain/LangGraph/Ray) is a plus
  • Experience with model deployment and monitoring in production environments (specific experience with real-time model inferencing is a plus)
  • Experience in fraud prevention, risk modeling, or identity verification is a plus

Pay

USD 140,000 - 170,000

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