Vice President - Data Science - BPO

Data Analysis
- Feature engineering
- Feature selection for traditional GLM models (e.g Lasso, ElasticNet, etc) and machine learning models
Machine Learning Algorithm Development
- Retooling/enhancing existing machine learning algorithms
- Implementing new machine learning algorithms that are available from the public domain
Fraud Detection Model Development
- Collaborate with fraud prevention/detection strategy teams and operations to understand business needs, data generating process, system capability, and potential impact of models.
- Design machine learning algorithms that can be used to improve the fraud prevention/detection scores
- Source data and apply feature engineering for model development and deployment
- Provide requirements and assist Information Technology for model deployment
- Document model solutions and address questions/concerns from model risk and control partners
- PhD./ Master's degree in Mathematics, Statistics, Economics, Computer Science, or related fields
- Expert in generalized linear models, unsupervised and supervised machine learning algorithms
- Demonstrated experience with Big Data tools like Hadoop & Spark
- Demonstrated proficiency in advanced analytical languages such as R, Python, Scala, SAS
- Experience with traditional database/system languages (e.g. SAS, SQL, etc.) to collaborate with other data analysts/systems
- Experience with implementing scalable machine learning/data mining algorithms making use of distributed/parallel processing
- Minimum 10 years of experience in Model development for Financial Services."