Full-Stack Data Scientist - Fraud & Identity Risk, Equity

kadence; United States; On-site; USD 180,000 - 220,000; Full time

Benefits offered by this job

Equity

Employer-paid health insurance

Job summary

Kadence is seeking a Full-Stack Data Scientist to develop models that identify identity fraud and support an expanding portfolio of financial risk products.

You will own projects across the complete data science lifecycle, including data acquisition, feature engineering, labeling, model development, experimentation, production deployment, and monitoring. This is a highly technical and product-focused role in a fast-moving startup.

Qualifications

• PhD with 2+ years of applicable experience or Master’s with 4+ years.
• Strong track record in data science or machine learning to solve complex business problems.
• Hands-on machine learning and statistics knowledge.
• Experience owning end-to-end data science projects from planning to deployment.
• Experience writing production code and automated tests.
• Ability to communicate technical outcomes to senior leadership.
• Startup experience and ability to thrive in a fast-paced environment.

Responsibilities

• Develop and maintain fraud detection models across the model lifecycle.
• Inform data acquisition, labeling, feature development, and model deployment decisions.
• Build foundational models for new fraud and financial risk products.
• Research emerging fraud patterns and new identity verification capabilities.
• Improve model performance by integrating new data sources and inventive features.
• Write production-quality code for real-time decision-making.
• Design analyses and present findings to influence product, risk, and sales decisions.
• Collaborate with engineering and data teams to access data and ensure quality.
• Communicate progress and recommendations to senior stakeholders.
• Develop deep expertise in identity fraud and financial risk.

Skills

Machine learning

Data science

Production code

End-to-end projects

Communication

Startup experience

Problem solving

Statistics

Data engineering

Education

PhD + 2 years

Master’s + 4 years

Tools

Production tests

Job description

Kadence is seeking a Full-Stack Data Scientist to develop models that identify identity fraud and support an expanding portfolio of financial risk products.

You will own projects across the complete data science lifecycle, including data acquisition, feature engineering, labeling, model development, experimentation, production deployment, and monitoring. This is a highly technical and product-focused role in a fast-moving startup.