Socure

Data Scientist II, Fraud and Deep Learning

Socure

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Salary

💰 $130,000 - $160,000 per year

Job Level

Mid-LevelSenior

Tech Stack

PythonPyTorchTensorflow

About the role

  • Lead, mentor, and grow a high-performing team of data scientists, fostering a collaborative and inclusive culture.
  • Design, implement, and optimize advanced deep learning model architectures (transformers, CNNs, LSTMs) to solve fraud and risk challenges.
  • Develop machine learning models using diverse data modalities (tabular, natural language, point clouds, images).
  • Champion feature discovery, feature engineering, and data mining initiatives to extract valuable signals from complex datasets.
  • Collaborate with cross-functional teams including product, engineering, and client-facing teams to deliver scalable AI solutions.
  • Ensure best practices in ML model development, evaluation, deployment, and monitoring.
  • Stay at the forefront of AI/ML and fraud/risk prevention technologies and incorporate emerging techniques.
  • Represent Socure as a subject-matter expert in external and internal forums as needed.

Requirements

  • Advanced degree (MS/PhD preferred) in Computer Science, Statistics, Mathematics, Engineering, or related field.
  • Proven, hands-on experience developing, training, and deploying deep learning models (transformers, CNNs, LSTMs) in production.
  • Demonstrated experience working with multiple data modalities, including tabular data, language/text, point clouds, and images.
  • Strong track record of managing, mentoring, and developing diverse teams of data scientists.
  • Deep understanding of machine learning best practices, data preparation, model evaluation, and deployment pipelines.
  • Expertise in feature discovery, feature engineering, and data mining techniques.
  • Proficiency in Python and modern ML frameworks (e.g., TensorFlow, PyTorch).
  • Excellent communication skills, with the ability to explain complex technical concepts to technical and non-technical stakeholders.
  • Experience in fraud prevention, risk management, fintech, or identity verification (preferred).
  • No visa sponsorship available now or in the future.