MoneyGram · 8 hours ago
Sr Data Scientist - US Remote
United States
Full-time
Remote
Mid, Senior Level
$130K/yr - $185K/yr
4+ years expMoneyGram is a global financial technology leader, empowering consumers and businesses to send and manage money across over 200 countries and territories. The role involves developing advanced fraud detection solutions using machine learning and data science techniques, including building models and deploying them into real-time production environments.
Financial Services
No H1B
Responsibilities
Build fraud detection models using gradient boosting and experiment with deep learning approaches where appropriate
Build supervised / unsupervised anomaly detection models on labeled and unlabeled data to identify outliers
Engineer features from transaction history, device fingerprints, behavioral signals, and identity data
Deploy models to production with real-time scoring and reason code generation
Design and execute champion/challenger experiments to validate model improvements
Build monitoring dashboards for model performance, drift detection, and feature stability
Analyze fraud patterns by corridor, customer segment, and transaction type to identify modeling opportunities
Investigate false positives and false negatives to drive continuous model improvement
Quantify trade-offs between approval rates and fraud losses at different threshold levels
Document model architecture, feature definitions, and performance characteristics
Support data labeling strategy and quality assurance with operations teams
Communicate insights and recommendations clearly to both technical and non-technical audiences
Qualification
Required
4+ years of experience in machine learning and data science
2+ years building production ML models in fraud, risk, payments, or financial services
Proven experience deploying and maintaining models in real-time production systems
Strong proficiency with gradient boosting frameworks (XGBoost, LightGBM, CatBoost)
Solid feature engineering skills—ability to extract signal from transactional and behavioral data
Production ML experience including model serialization, deployment, and performance monitoring
Proficient SQL for working with large datasets (BigQuery, Snowflake, or similar)
Proficiency in Python: pandas, NumPy, scikit-learn, and familiarity with deployment tools
Understanding of model explainability (SHAP values, feature importance, gain importance)
Experience with A/B testing or champion/challenger experimental design
Understanding of fraud detection concepts: false positive/negative trade-offs, precision/recall, threshold optimization
Familiarity with common fraud signals (velocity, device, identity, behavioral)
Ability to translate model outputs into business impact (approval rates, loss rates, customer friction)
Preferred
Experience with payment fraud, account takeover, or identity fraud specifically
Familiarity with identity verification signals (device fingerprinting, phone/email risk)
Experience with decisioning platforms (Oscilar, Datavisor, Actimize, or similar)
Background in anomaly detection or unsupervised learning for emerging fraud patterns
Benefits
Remote first flexibility
Generous PTO
13 Paid Holidays
Medical / Dental / Vision Insurance
Life, Disability, and other benefits
401k with competitive Employer Match
Community Service Days
Generous Parental Leave
Company
MoneyGram
MoneyGram connects the world by making the movement of money across borders seamless, affordable and secure for everyone.
1001-5000 employees
Funding
Current Stage
Late StageLeadership Team
Alex Holmes
CEO
Joe Vaughan
Chief Technology Officer
Recent News
Business Standard India
2025-07-02
2025-06-17
2025-06-17
Company data provided by crunchbase