Back
High due to Tier-1 brand, popular data science title, mid-level experience band, and metro locations.
Medium — core ML and statistical skills are transferable, but credit-card domain and governance increase specificity.
High due to explicit years requirement plus mandatory ML/PySpark/SQL skills and model governance experience.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Own and deliver multiple complex analytic projects involving model building, validation, implementation, and governance for North America Consumer Cards portfolios.
Develop client-centric analytic solutions addressing business problems in new customer acquisition, customer management, retention, product development, pricing, payment optimization, and digital journeys.
Work with large datasets using Python, PySpark, SQL, and statistical techniques to build predictive and machine learning models aligned with business needs, while ensuring compliance with Citi standards.
Bachelor's degree with 4+ years or Master's degree with 2+ years experience in data analytics or PhD.
Hands-on experience with PySpark/Python, strong SQL skills, and 2-4 years working with machine learning and statistical modeling techniques.
Strong statistical analysis background and experience with large, multiple datasets and data warehouses.
Experience validating and maintaining deployed models in production; experience in Credit Cards preferred but not mandatory.
Domain expertise in North America Consumer Cards analytics, including marketing, risk, digital, or AML specialization.
Ability to manage multiple stakeholders and communicate complex technical concepts to senior management effectively.
Experienced in applying machine learning and deep learning techniques to real-world business problems with strong project management and coaching capabilities.