Socure is looking to solve the problem of verifying 100% of good identities in real time and eliminating identity fraud from the internet by developing advanced AI/ML solutions for fraud detection, risk assessment, and identity verification.
Requirements
- Previous hands-on experience developing, training, and deploying deep learning models, such as transformers, CNNs, and LSTMs, in a production environment.
- Demonstrated experience working with multiple data modalities, including (but not limited to) tabular data, language/text, point clouds, and images.
- 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).
Responsibilities
- Lead, mentor, and grow a high-performing team of data scientists, fostering a collaborative and inclusive culture.
- Coach teams to design, implement, and optimize advanced deep learning model architecture, such as transformers, CNNs, and LSTMs, to solve real-world fraud and risk challenges.
- Drive the development of machine learning models using a wide range of data types and input modalities, such as tabular data, natural language, point clouds, and images.
- Champion feature discovery, feature engineering, and data mining initiatives to extract valuable signals from complex and high-dimensional datasets.
- Collaborate with cross-functional teams including product, engineering, and client-facing teams to deliver robust, scalable AI solutions.
- Ensure best practices in ML model development, evaluation, deployment, and monitoring.
- Stay at the forefront of advancements in AI, machine learning, and fraud/risk prevention technologies, incorporating emerging techniques into our solutions.
Other
- Experience in the fraud prevention, risk management, fintech, or identity verification space.
- Strong track record of managing, mentoring, and developing diverse teams of data scientists.
- Excellent communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
- Advanced degree (MS/PhD preferred) in Computer Science, Statistics, Mathematics, Engineering, or related field.
