Data Scientist

Who you are

• 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

What the job involves

• 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
• 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

Benefits

• Health: Comprehensive medical coverage, including vision, dental, and FSA
• Parental Leave: Generous leave allowance for parents-to-be
• 401k: Pre-tax savings for retirement
• Life Insurance: Protect your family in case of emergency
• PTO: Take as much time as you need, when you need it
• 100% Remote: Work from anywhere anytime, whatever suits your lifestyle
• WFH Allowance: Generous reimbursement program to maximize your WFH setup
• Deskpass: Work in an office environment whenever you feel the need
• Mental Health Provider: Connect with clinicians when you need it
• Learning & Development: Self-education allowance & free career coaching
• Employee Assistance Program "EAP": Lifestyle resources available as well as additional mental health resources
• Fertility Provider: Family planning solutions for those interested
• Personal Legal Support: Significant discounts with RocketLawyer