Data Scientist/ Machine Learning
Published | March 1, 2023 |
Location | West Mclean, United States of America |
Category | Machine Learning |
Job Type | Full-time |
Description

- Program Overview: He is in the Mode and Infrastructure Team within Credit Risk to develop and move risk models into production risk platform to utilize data and deployment of models. Build and manage a team of ~20 Data Scientists, Quants and Data Analysts to develop, implement and transform Capital One Credit Risk Models and Loss Forecasting System for Retail Portfolio (Mortgage/Card/Auto) through advanced analytics and innovations to enhance the enterprise's decision making;
- Credit Risk Modeling and Implementation for Retail Portfolios (Auto, Card & Mortgage);
- Loss Forecasting, ACL, CECL;
- CCAR and Stress Testing;
- Cash Flow Engine;
- Model Monitoring and Model Calibration/Adjustment;
Required Skills:
- Must Have: Python programming, AWS, Spark, Machine modeling
- Nice to have: SQL, snowflake, tableau
- Good understanding of Credit Risk models not viewed but working very closely with the model teams
- Data Scientist and engineering team deploying models care about inefficiencies need to streamline the process instead of create solutions
- Leverage tools and tech for data visualization for monitoring and performance dashboard development data visualization would be key
- Mostly working utilizing Python, Pyspark, AWS and Flask have models written in Spark version of R moving from R to Python
- Python experience is key
- AWS experience is required
- Spark is a must have
- Expecting 3-5 years of experience rates need to reflect the levels of experience
- Data Scientist who knows modeling and Python connect the models, deploy the models and optimize them financial engineer
- BAU monitoring in Python - understanding models
- Help to be able to convert or optimize modeling code or exclusion into a more efficient way converting spark in to Task and Pyspark converting and optimizing code
- Converting and intent must be correct, testing is key.
- Previous FinTech experience is a nice to have
Tech stack:
- Python
- Spark
- Machine Learning modeling
- Credit Risk Modeling
- Predictive Modeling