Data Scientist • Mid-Level

Who you are

You have a strong background in data science with a focus on fraud detection and risk management — your experience includes designing and implementing advanced deep learning models that tackle complex challenges. You are proficient in Python and have hands-on experience with various machine learning frameworks, enabling you to build impactful solutions. Your analytical mindset allows you to work with diverse data types, including tabular data, natural language, and images, ensuring comprehensive model development. You thrive in collaborative environments, working closely with cross-functional teams to drive project success and functional productivity. You are detail-oriented and take ownership of your tasks, ensuring high-quality outcomes in your work.

What you'll do

As a Data Scientist II at Socure, you will design, develop, and implement advanced deep learning models, including transformers, CNNs, and LSTMs, to address complex fraud and risk challenges. You will build and optimize models using a variety of input data types, ensuring that your solutions are robust and effective. Your role will involve collaborating with colleagues to deliver impactful solutions for fraud detection and identity verification. You will have the autonomy to manage your day-to-day work while contributing to diverse projects that enhance the company's mission of building identity trust infrastructure. Your contributions will directly impact the effectiveness of fraud prevention strategies and risk management processes.

What we offer

At Socure, you will be part of a high-performing team that values innovation and responsibility. We offer a supportive work environment where you can grow your skills and make a significant impact on the digital economy. You will have the opportunity to work on cutting-edge technologies and contribute to projects that help businesses and governments combat fraud effectively. We encourage you to apply even if your experience doesn't match every requirement, as we value diverse perspectives and backgrounds.