Expert Data Scientist, Fraud Risk Detection

About Our Client:

The organization operates globally in data and technology, serving diverse sectors such as financial services, healthcare, automotive, agribusiness, and insurance. It addresses challenges in data utilization by investing in advanced technologies and expertise to unlock data's potential, employing a large workforce across multiple countries.

About the Opportunity:

The EXPERT DATA SCIENTIST, FRAUD RISK DETECTION is responsible for developing and implementing fraud detection models to identify high-risk activities while minimizing disruption to legitimate customers. This role involves analyzing emerging fraud patterns, creating features, and collaborating with senior data scientists and engineers to deliver production-ready machine learning solutions that enhance fraud risk management.

Responsibilities:

• Analyze large datasets to identify fraud patterns and develop fraud labels.
• Formulate clear hypotheses and analytical plans from ambiguous fraud and risk problems.
• Develop machine learning models targeting fraud detection in account opening, takeover, and identity risk.
• Evaluate models using various performance metrics including ROC/AUC and fraud capture rates.
• Create and validate predictive features from diverse data sources.
• Write efficient, tested Python and PySpark code for model and feature deployment.
• Monitor model and feature performance and detect fraud pattern shifts.
• Present analyses on model behavior, risks, and recommendations.
• Adhere to standards for data privacy, model documentation, explainability, validation, and governance.

Requirements:

• Minimum of 3 years in data science, machine learning, or related quantitative fields.
• Bachelor's or advanced degree in computer science, statistics, engineering, data science, or related disciplines.
• Experience developing fraud detection or adversarial risk models.
• Proven ability to create meaningful fraud-related features.
• Proficiency in Python, PySpark, and common machine learning tools.
• Understanding of supervised learning, model evaluation, and calibration.
• Experience managing challenges like class imbalance, delayed labels, and model drift in fraud contexts.
• Experience deploying models into production environments.

Pay Range and Compensation Package:

• Compensation ranges from USD 103,669 to USD 179,693 annually.

Benefits & Perks:

• Medical insurance
• Dental insurance
• Vision insurance
• 401(k) plan with matching contributions
• Flexible work environment including remote, hybrid, or in-office options
• Flexible time off including volunteer time off, vacation, sick leave, and 12 paid holidays

Equal Opportunity Statement: Our client is an equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, or national origin.

Note:

RemoteHunter is a recruitment partner of this role. Please note that all employment decisions, including candidate assessment, interviews, hiring, compensation, and employment terms, are made exclusively by the hiring employer.