Senior - Data Scientist

Advanced Analytics – Should independently extract data, checks integrity, handles missing values/outliers, and performs preprocessing. Conducts EDA to guide modeling. Applies clustering/factor analysis, engineers features, and builds models (GLMs, tree-based, neural nets). Validates models, fixes issues, sizes impact, presents results, and supports implementation. - (40%)

Collaboration & Communication – Effectively translates analytical insights into actionable recommendations for both managerial review and cross-functional stakeholders. Demonstrate strong communication with internal partners. Build knowledge of credit card ops, banking, finance, loyalty, retail, and regulations. Collaborate with data scientists to share best practices and innovations. - (30%)

Data Science Innovation – With guidance, research trends in tools, algorithms, platforms, and data to enhance modeling. Test use cases for new methods and provide feedback. Conduct research to improve predictive modeling techniques and outcomes. - (20%)

Model Risk Management - Build knowledge of model risks and regulations. Apply first line of defense controls to reduce risk. Prepare governance documentation and archive data, scripts, and results. Collaborate with risk partners on validation/audits. Complete remediation per governance requirements. - (10%)

Minimum Qualifications

Bachelor’s Degree in statistics, mathematics, engineering, data science, economics, computer science, or another quantitative field of study.

Preferred Qualifications

Master’s Degree in statistics, mathematics, engineering, data science, economics, or computer science.Experience in developing statistical models/machine learning models and conducting data mining to solve business problems.

5-8 years of experience in the software field.

Experience in extracting and processing large files/data sets.

Experience interpreting model results and translating insights into business recommendations.

Skills

Data Analytics