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.