Data Scientist

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

Salary: $180,000–$220,000 base salary, plus equity and benefits

Company Overview

Our client is a fast-growing, venture-backed technology company developing advanced identity verification, fraud detection, and financial risk solutions.

Its real-time products have been used to verify hundreds of millions of identities, helping financial institutions detect sophisticated fraud and transact with greater confidence. The company operates as a digital-first organization with teams distributed across the United States.

The Role

We are looking for 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 position. You will research emerging fraud patterns, develop new modeling capabilities, write production-ready code, and deliver analysis that influences product, operational, and commercial decisions.

The role is best suited to someone who enjoys solving varied, open-ended problems and wants significant ownership in a fast-moving startup environment.

Responsibilities

• Develop and maintain fraud detection models throughout the complete model lifecycle.
• Inform data acquisition, labeling, feature development, model training, experimentation, deployment, and monitoring decisions.
• Build foundational models for new fraud and financial risk products.
• Research emerging forms of fraud and identify opportunities to develop new identity verification capabilities.
• Improve model performance by integrating new data sources and developing inventive features.
• Write reliable, production-quality code used for real-time decision-making.
• Design, conduct, and present analyses that inform product development, risk operations, data acquisition, marketing, and sales.
• Partner with engineering, risk operations, and data teams to access necessary information and maintain data quality.
• Communicate project progress, technical findings, and recommendations to senior stakeholders.
• Develop deep expertise in identity fraud and financial risk.

Requirements

• A relevant PhD with at least two years of applicable professional experience, or a relevant master’s degree with at least four years of experience.
• A strong track record of solving complex or high-profile business problems using data science or machine learning.
• Strong practical knowledge of machine learning and statistics.
• Experience owning end-to-end data science projects, from planning and defining success metrics through delivering production systems, analyses, or strategic recommendations.
• Experience writing production code and automated tests.
• Ability to communicate technical outcomes clearly to senior leaders and cross-functional stakeholders.
• Strong attention to detail and sound judgment when making high-impact decisions.
• Experience working in a startup environment.
• Ability to thrive in a fast-paced environment and solve varied, high-impact, open-ended problems.
• Must live in the United States and be legally authorized to work in the United States.

Preferred Qualifications

• Experience with identity verification, fraud detection, fintech, financial services, or an adjacent industry.
• Familiarity with advanced or state-of-the‑art machine learning techniques.
• Base salary of $180,000–$220,000
• Equity
• Employer-paid health insurance for employees and their dependents