WPC Apple Card Data Scientist

Summary

Apple is a place where extraordinary people gather to do their best work. Together we craft products and experiences people once couldn’t have envisioned — and now can’t imagine living without. If you’re excited by the idea of making a real impact and joining a team where we pride ourselves in being one of the most diverse and expansive companies in the world, a career with Apple might be your perfect job.

Description

The Wallets, Payments, and Commerce (WPC) team at Apple is looking for a full-stack Data Scientist who is passionate about crafting and implementing data solutions that have a direct and measurable impact on Apple customers. In this role, you will help chart the future direction of Apple Card by identifying and investigating new opportunities, projecting future results, and ensuring the business can execute against its long-term strategy.
You will partner directly with product, marketing, finance, and credit teams, working cross-functionally to deliver results, as well as working with external partners such as issuing banks to help deliver on our product strategy and roadmap.
You should have experience and subject matter expertise in financial modeling, payments, banking, credit, risk operations, data science, and finance. Previous experience working in the credit card industry at an issuer, network or co-brand partner is highly preferred. Experience with a variety of financial products is a plus.

Preferred Qualifications

Advanced degree in Applied Econometrics, Statistics, Machine Learning, Analytics, Mathematics, Operations Research, Industrial Engineering, or related field preferred.
Previous experience working in the credit card industry at an issuer, network or co-brand partner is highly preferred
Experience with a variety of financial products

Minimum Qualifications

Minimum of bachelor’s degree in engineering, data science, economics, statistics, computer science, or related quantitative field
Minimum of 8 years of experience with a proven track record of success in data science roles focused on financial modeling, business analysis, finance, and data analysis
Deep understanding of product valuation modeling and marginal decisioning
Expert data wrangler in Python (e.g., Pandas, Polars) with experience working with relational databases, including SQL, and large-scale distributed systems such as Redshift
Proficient in cloud data platforms such as Snowflake and Databricks
Strong experience in building scalable production ready workflows, end-to-end ETL pipelines and predictive models that enable data-driven decisions
Exceptional data visualization and storytelling abilities, capable of translating complex analyses into clear, executive-ready insights
Excellent written and verbal communication skills, adept at translating technical results into clear, compelling narratives for non-technical and executive audiences
Highly organized, self-driven, and effective at prioritizing and delivering multiple initiatives under tight timelines