Fraud Detection Data Scientist — ML in Production

Democrance; Town of Poland (NY); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Salary and benefits (pension)

Health insurance

Annual bonus

Other benefits

Job summary

Moniepoint is seeking a Data Scientist to combat fraud by building models, experiments, and detection systems used across our platform. You will prototype, deploy, and monitor ML solutions that protect millions of customers and merchants.

You will design experiments, uncover fraud signals, and translate results into real-world mitigations in collaboration with engineers, product managers, and analysts.

Qualifications

• Strong foundation in statistics and quantitative methods.
• 3+ years of data science, decision science, or risk analytics in fraud, payments, or financial crime.
• Hands-on experience building and deploying ML models in production.]
• Experience with fraud/risk or financial services is a plus.
• Solid grounding in experiments, inference, model evaluation, and feature engineering.

Responsibilities

• Prototype, evaluate, and maintain ML models for fraud detection and their retraining cycles.
• Design experiments to measure impact of fraud interventions balancing CX and loss reduction.
• Size fraud typologies across product lines to guide prioritization and investment.
• Build and maintain anomaly detection systems to surface novel fraud vectors.
• Collaborate with fraud ops, engineers, product, and data analysts to translate outputs into mitigations.

Skills

Python

SQL

Statistics

Experimentation

Communication

Education

Bachelor's or Master’s in Statistics/Math/CS/Engineering

Job description

Moniepoint is seeking a Data Scientist to combat fraud by building models, experiments, and detection systems used across our platform. You will prototype, deploy, and monitor ML solutions that protect millions of customers and merchants.

You will design experiments, uncover fraud signals, and translate results into real-world mitigations in collaboration with engineers, product managers, and analysts.