What are the responsibilities and job description for the Sr. Manager - Data Science & Analytics position at Radial Inc.?
Radial, Inc seeks Sr. Manager - Data Science & Analytics in King of Prussia, PA.
Job Duties : Develop, maintain, evaluate, enhance, and communicate real-time and offline Machine Learning (ML) models for fraud detection. Build and deploy end-to-end ML pipelines and manage MLOps. Optimize ML models for performance, scalability, and cost-effectiveness. Build and maintain anomaly detection algorithms to identify suspicious activities and patterns indicative of fraud. Participate in on-call rotations to provide timely support for critical issues with deployed ML models and anomaly detection processes. Implement data quality monitoring systems to detect anomalies and inconsistencies in incoming data streams. Develop and enhance rule-based strategies to complement ML models for fraud detection. Proactively identify new methods and processes to increase revenue and reduce cost and friction. Work closely with Technology team to build Radial’s Data Science framework. Support cloud transformation to enhance Radial’s Data Science/Machine Learning capabilities. Perform ROI analysis and business case justification / review for new vendor/partner. Regularly report that shows the status and next steps for all Fraud Risk Technology Partners. Serve as main point of contact for off-shore (IDC) and in-house Data Scientist Resources during on and off hours. Manage a team of professionals in fraud decision science, fraud detection, fraud risk analysis, and fraud data science. Telecommuting Permitted .
Minimum Requirements : Master’s degree, or foreign equivalent, in Data Science, Data Analytics, or a closely related quantitative field and three (3) years of experience in the job offered or three (3) years of experience in the field of Machine Learning, Business/Data Analytics, Statistics, or related occupation
Special Skills :
Apply through the career’s website: https://radial.my.salesforce-sites.com/careers with reference to: Job#: JO-2603-11235.
Job Duties : Develop, maintain, evaluate, enhance, and communicate real-time and offline Machine Learning (ML) models for fraud detection. Build and deploy end-to-end ML pipelines and manage MLOps. Optimize ML models for performance, scalability, and cost-effectiveness. Build and maintain anomaly detection algorithms to identify suspicious activities and patterns indicative of fraud. Participate in on-call rotations to provide timely support for critical issues with deployed ML models and anomaly detection processes. Implement data quality monitoring systems to detect anomalies and inconsistencies in incoming data streams. Develop and enhance rule-based strategies to complement ML models for fraud detection. Proactively identify new methods and processes to increase revenue and reduce cost and friction. Work closely with Technology team to build Radial’s Data Science framework. Support cloud transformation to enhance Radial’s Data Science/Machine Learning capabilities. Perform ROI analysis and business case justification / review for new vendor/partner. Regularly report that shows the status and next steps for all Fraud Risk Technology Partners. Serve as main point of contact for off-shore (IDC) and in-house Data Scientist Resources during on and off hours. Manage a team of professionals in fraud decision science, fraud detection, fraud risk analysis, and fraud data science. Telecommuting Permitted .
Minimum Requirements : Master’s degree, or foreign equivalent, in Data Science, Data Analytics, or a closely related quantitative field and three (3) years of experience in the job offered or three (3) years of experience in the field of Machine Learning, Business/Data Analytics, Statistics, or related occupation
Special Skills :
- Python for Data Analysis, Machine Learning, API development
- SQL
- AWS SageMaker, API gateway, Lambda, S3, EC2
- Developing and implementing machine learning models in risk assessment/scoring engine, and optimizing risk scoring rules
- Scikit-learn, Tensorflow, Pytorch
- Git, Jira, Confluence
- Statistical analysis and experimental design
- Modeling Decision Tree, XGBoost, LGBM, SHAP
- Docker, Jenkins
- Tableau
Apply through the career’s website: https://radial.my.salesforce-sites.com/careers with reference to: Job#: JO-2603-11235.