Senior Data Scientist - Fraud Risk & Growth (Remote US)

Ovise Limited; United States; Remote; USD 190,000 - 250,000; Full time

Benefits offered by this job

Equity

Comprehensive benefits

Healthcare

Retirement matching

Flexible PTO

Home office allowance

Job summary

Ovise Limited is seeking a Senior Data Scientist to drive end-to-end data science initiatives from data collection and feature engineering to modelling, deployment and monitoring. You will build robust ML models powering real-world risk decisions and collaborate with engineering, product, and operations teams.

The role emphasizes research of fraud patterns, production-grade Python development, and clear communication of insights to influence product strategy and business growth.

Qualifications

• 4+ years of ML experience with strong academic background.
• Proficient in Python and production ML workflows.
• Experience taking data science projects from concept to production.
• Excellent communication and ability to engage senior stakeholders.
• Detail-oriented and proactive in ambiguous problems.

Responsibilities

• Own the full data science lifecycle from data acquisition to modelling, deployment and monitoring.
• Build and improve ML models powering real-world risk decisions.
• Research emerging fraud patterns and support new product development.
• Write production-quality Python code and conduct rigorous statistical analysis.
• Present insights that influence product strategy and business growth.
• Collaborate closely with engineering, product and operations teams.

Skills

Machine learning

Statistics

Production ML

Communication

Stakeholder engagement

Education

PhD

Masters

Bachelor's

Tools

Python

Job description

Ovise Limited is seeking a Senior Data Scientist to drive end-to-end data science initiatives from data collection and feature engineering to modelling, deployment and monitoring. You will build robust ML models powering real-world risk decisions and collaborate with engineering, product, and operations teams.

The role emphasizes research of fraud patterns, production-grade Python development, and clear communication of insights to influence product strategy and business growth.