Data Scientist II, Fraud & Risk

Socure; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Impactful, cutting‑edge problems

Inclusive, innovative culture

Competitive compensation + equity + 福利

Job summary

Socure is seeking a Data Scientist II to join the Fraud & Risk Data Science team. You will design and deploy deep learning models for fraud detection and identity verification, working hands‑on with transformers, CNNs, and LSTMs across multiple data modalities.

You will take ownership of tasks, collaborate across teams, and deliver impactful results in a fast‑paced environment focused on real‑time inference and production readiness.

Qualifications

• 2–4 years hands‑on experience building and deploying deep learning models (transformers, CNNs, LSTMs).
• Experience with multiple data modalities (tabular, text, images, point clouds) and production ML pipelines.
• Strong Python proficiency and familiarity with ML libraries (PyTorch, TensorFlow, scikit‑learn).
• Experience deploying and monitoring models in production, including real‑time inferencing is a plus.

Responsibilities

• Design, develop, and deploy advanced deep learning models to combat fraud and assess risk.
• Work with diverse data types and modalities to improve detection and verification accuracy.
• Own tasks end‑to‑end from data exploration to model deployment and monitoring.
• Collaborate across teams and translate results for both technical and non‑technical audiences.
• Stay current with AI advances and apply cutting‑edge approaches to real‑world problems.

Skills

Python

PyTorch

TensorFlow

Scikit-learn

Deep learning

Transformers

Data pipelines

Education

Bachelor's degree in CS/Stats/Math/Engineering

Master's degree in related field

Tools

LangChain

LangGraph

Ray

Job description

Why the company?

the company is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day.

We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won’t be your place. If you want to help build the future of identity with a team that holds a high bar for itself — keep reading.

Role Overview

We are seeking a skilled and motivated Data Scientist II to join our Fraud & Risk Data Science team. As an individual contributor, you will have autonomy in your day-to-day work and play an important role in driving functional productivity and project success. You will work hands-on with advanced deep learning models, collaborating with colleagues to deliver impactful solutions for fraud detection, risk management, and identity verification. This position provides the opportunity to contribute to diverse projects and collaborate within a supportive, high-performing team.

Key Responsibilities

• Design, develop, and implement advanced deep learning models, including transformers, CNNs, and LSTMs, 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.
• Take ownership of assigned tasks, executing technical and functional activities to support project goals with minimal supervision.
• Participate in all stages of the machine learning lifecycle: data exploration, feature engineering, model training, evaluation, and deployment.
• Collaborate effectively 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 AI and machine learning, applying innovative approaches to real-world problems.
• Communicate results and insights clearly to both technical and non-technical audiences.

Qualifications

• 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.
• 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.
• Proficiency in Python and major ML libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
• Foundational 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.
• Strong problem-solving skills, with the ability to work independently on straightforward tasks and contribute effectively to project objectives.
• Demonstrated ability to collaborate in a diverse, cross-functional team environment.
• Excellent written and verbal communication skills.
• Experience in fraud prevention, risk modeling, or identity verification is a plus.

Why the company?

• Work on impactful, challenging problems using cutting-edge technology.
• Collaborate with talented colleagues in an inclusive, innovative culture.
• Competitive compensation, equity, and benefits.
• Opportunities for professional growth and skill development.

the company is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your the company recruiting partner directly.

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