Payment Optimization Data Scientist II
US OH CIN 8500, United States
USD 99K-152K (estimate) Mid-level Full Time
Tasks
- Analyze payment data and extract insights
- Apply multi armed bandits and reinforcement learning for optimization
- Build and integrate features into Spark based model workflows
- Consolidate and normalize payment data into feature sets
- Design and analyze A/B tests
- Develop and deploy supervised machine learning models
- Document models and track performance
- Execute segmentation analysis to improve data quality
- Monitor and mitigate data drift and model drift
- Perform causal inference for continuous optimization
- Present analyses to stakeholders
- Run large scale feature extraction and processing
- Transform complex datasets into usable formats
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | AUC | Apache Spark | B testing | BigQuery | CatBoost | Causal Inference | Clustering | DBSCAN | Data Drift | Data Drift Detection | Data Normalization | Data segmentation | Databricks | Drift Detection | Dynamic Transaction Retry | Feature Engineering | Intelligent Payment Orchestration | K-Means | Machine Learning | Model Monitoring | Multi-Armed Bandits | MySQL | Payment orchestration | Python | R | Reinforcement Learning | SAS | SQL | Scala | Series analysis | Snowflake | Statistical modeling | Supervised Learning | Time Series | Time Series Analysis | Time of Day | Time of Day Optimization | XGBoost
Education
Roles
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