Data Modeler II

📋 Description

• Deliver high quality analytical and value-added services for clients within timelines.
• Engage Business/Technical Consultants and delivery teams for shared understanding.
• Use analysis and customer insights to develop value propositions for customers.
• Apply data mining, statistics and ML to build predictive models integrated with products.

🎯 Requirements

• Understanding of ML techniques/algorithms (Gradient Boost, KNN).
• Modelling frameworks: Linear Regression, Logistic Regression, Decision Tree.
• Hands-on Python, PySpark or SAS; statistical analysis basics.
• Understanding of banking/portfolio management is a plus.
• Credit bureau knowledge is a plus.

🎁 Benefits

• Inclusive, people-first culture and award-winning workplace.
• Equal Opportunity employer; accessibility accommodations available.