Manager, Data Science - US Remote at MoneyGram

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

03 Apr, 26

Salary

200000.0

Posted On

03 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Science, Fraud Detection, Risk Management, Feature Engineering, SQL, Python, Model Monitoring, Decision Management, Real-Time Systems, Model Explainability, Behavioral Patterns, API Integration, Data Manipulation, Rule-Based Systems, Champion/Challenger Frameworks

Industry

Financial Services

Description

***This role is 100%25 remote and can be located anywhere in the US Did you know there are 1.4 billion1 people in the world that are financially underserved by traditional banks? 🤔 In many cases, people that depend on remittances being sent or received, often across different countries. Sometimes even across different continents. MoneyGram impacts the daily life of 1.5 million customers, connecting families and businesses across borders. By relying on a vast network of agents, by being present in 200+ different countries, and by developing cutting-edge payment technology, MoneyGram is paving the way for global financial fairness and inclusion! Will you join us in our journey? About the Manager, Data Scientist The role is responsible for designing, developing, and deploying production fraud detection models that score transactions in real time. This individual will co-own the end-to-end data science roadmap for transaction fraud and risk, build and maintain feature pipelines leveraging transaction data, device signals, behavioral patterns, and identity attributes, and lead the transition from rules-based fraud detection to a model-first decisioning architecture. They will design the interaction between models and rules, implement champion/challenger frameworks to optimize performance, and create monitoring systems for model drift, feature distribution shifts, and rule effectiveness. Additional responsibilities include generating explainability outputs for every model decision, mentoring a small team of data scientists while remaining hands-on, partnering with Risk Intelligence to align strategies with business objectives, and presenting performance analysis and strategic recommendations to leadership. What You Will Do: · Design, develop, and deploy production fraud detection models that score transactions in real-time · Co-own the end-to-end data science roadmap for transaction fraud and risk · Build and maintain feature pipelines using transaction data, device signals, behavioral patterns, and identity attributes · Lead the transition from rules-based fraud detection to model-first decisioning architecture · Design the interaction between models and rules; determining when models make primary decisions versus rules · Implement champion/challenger frameworks to continuously test and improve both model and rule performance · Create monitoring systems for model drift, feature distribution shifts, rule effectiveness, and overall system performance · Generate reason codes and explainability outputs for every model decision · Mentor and lead a small team of data scientists while remaining hands-on with development · Partner with Risk Intelligence team to align model and rule strategies with business objectives · Present performance analysis, trade-off recommendations, and strategic roadmaps to leadership Who We’re Looking For: Experience · 7+ years of progressive experience in machine learning, data science, or quantitative risk · 4+ years building production ML models in fraud, risk, payments, or financial services · 3+ years working with rule-based fraud detection systems, including rule design, tuning, and performance optimization · 2+ years leading or mentoring data scientists or analysts in a technical capacity · Demonstrated track record deploying and maintaining models in real-time production systems Technical Skills · Expert-level proficiency with gradient boosting frameworks (XGBoost, LightGBM, CatBoost) · Strong experience with rule engines and decision management systems · Advanced feature engineering for transactional and behavioral data · Production ML deployment including model serialization, API integration, and latency optimization · Advanced SQL for large-scale data manipulation (BigQuery, Snowflake, or similar) · Python fluency: pandas, NumPy, scikit-learn, and model deployment frameworks · Experience with model monitoring, drift detection, and automated retraining pipelines · Understanding of model explainability techniques (SHAP values, feature importance, gain importance) Domain Knowledge · Strong understanding of fraud patterns: account takeover, identity fraud, transaction fraud, or similar · Experience designing hybrid systems where models and rules work together effectively · Strong grasp of rule lifecycle management: creation, testing, deployment, monitoring, and retirement · Familiarity with identity and risk signals (device fingerprinting, phone/email intelligence, velocity patterns) · Experience balancing approval rates against fraud losses—you understand the business trade-offs Preferred · Experience with decisioning platforms (Oscilar, Datavisor, Actimize, or similar) · Background in money transfer, remittance, or cross-border payments · Experience leading organizations through transitions from rules-heavy to model-first fraud detection Location: · This position will be remotely based in the United States Here Are Some Reasons You Will Love Working At MoneyGram! · 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 Anticipated Base Pay: $150,000 – $200,000 + participation in our annual bonus plan. The salary/pay rate listed is a good faith determination that may be offered to a successful applicant for this position at the time of this job advertisement based on company hiring process and budget for this role and may be modified in the future. Actual compensation may vary from posting based on geographic location, work experience, education and/or skill level. MoneyGram does not sponsor US work authorizations for this job position including H-1B, O-1, and TN. MoneyGram also does not hire F-1’s working on EAD for this position. About MoneyGram MoneyGram International, Inc. is a global financial technology leader, empowering consumers and businesses to send and manage money across over 200 countries and territories. With an industry-leading app and one of the world’s largest cash distribution networks, MoneyGram processes more than $200 billion annually, serving over 50 million people. A pioneer in blockchain technology, the company enables customers to buy, sell, and hold digital currencies, with over 50%25 of transactions now digital. Headquartered in Dallas, Texas, MoneyGram is celebrated for its strong culture, earning the Top Workplaces USA award three years in a row. Date Science

Responsibilities

The role involves designing, developing, and deploying production fraud detection models that score transactions in real-time. It also includes mentoring a small team of data scientists and aligning strategies with business objectives.