Staff/Senior Data Scientist, Algorithm (Risk & Fraud) in United States at Jobgether

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Staff/Senior Data Scientist, Algorithm (Risk & Fraud) in the United States.

This role sits at the core of a global risk platform team focused on detecting, preventing, and mitigating fraud across large-scale financial and payment systems. You will design and deploy advanced machine learning models that directly protect users, transactions, and digital financial infrastructure in a fast-evolving threat landscape. Working in a highly collaborative, product-driven environment, you will transform complex business challenges into scalable ML solutions that operate in real time. The position offers the opportunity to build end-to-end risk algorithms, influence platform architecture, and drive measurable business impact. You will partner closely with engineering, product, and data teams to enhance fraud detection systems at global scale. This is a high-visibility role where your work directly strengthens trust and security across international financial flows.

In this role, you will develop and operationalize machine learning solutions that address complex fraud and risk challenges across global payment systems. You will own the full ML lifecycle, from problem definition to deployment and continuous improvement, ensuring models deliver strong business impact.

• Translate business and risk challenges into machine learning problems and scalable algorithmic solutions.
• Build, train, and deploy ML models using advanced feature engineering, data pipelines, and experimentation frameworks.
• Analyze risk patterns and fraud behaviors to identify system weaknesses and propose data-driven solutions.
• Develop and enhance ML platforms and tools that streamline model development and deployment workflows.
• Collaborate with cross-functional teams to integrate models into production systems and real-time risk decisions.
• Continuously monitor model performance and iterate based on evolving fraud patterns and business needs.

The ideal candidate is a strong machine learning practitioner with experience solving real-world problems in high-scale environments, particularly within risk, payments, or e-commerce domains. You are comfortable working end-to-end on ML systems and translating data insights into production-ready solutions.

• 3+ years of experience using machine learning frameworks such as scikit-learn, TensorFlow, PyTorch, or Keras.
• Bachelor’s degree or higher in Computer Science, Engineering, Mathematics, or a related technical field.
• Strong programming skills in Python and SQL for data manipulation and model development.
• Experience in payment risk, fraud detection, or e-commerce risk is a strong plus.
• Exposure to applying ML or LLM-based approaches to real-time systems is highly desirable.
• Strong analytical thinking and ability to solve complex, ambiguous technical problems.
• Experience working in cross-functional teams in a product-driven environment.

• Competitive compensation package including base salary, bonus, and equity.
• Comprehensive medical, dental, and vision insurance coverage (for eligible employees).
• Paid time off, including vacation days and company holidays.
• Retirement savings plan and additional financial wellness benefits.
• Opportunity to work on high-impact global financial risk and fraud systems.
• Fast-paced, innovative environment with strong ownership and career growth opportunities.
• Collaborative, international team culture across multiple global offices.