Summary
Imagine what you could do here. At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and curiosity to your job and there’s no telling what you could accomplish. Do you love thinking analytically? Just as our customers find value in Apple products, the Finance group finds value for both Apple and its shareholders.
As a machine learning engineer in Finance, you’ll play an integral and global role in building the data foundations, services, and platforms used for delivering insights and automating decisions for Apple’s Finance organization.
Description
This role will require you to be collaborative by learning intra-team and business process in order to build infrastructure and services to enable an effective Machine Learning practice. You will help lead the charge by developing a strong ML Ops process in a dynamic Finance environment where you will deal with unique challenges specific to Finance organizations, such as SOx and regulatory compliance. Your ability to instill and proliferate strong software engineering practices into team data science and machine learning processes will be critical.
You are a quantitatively and technically inclined individual with an applied data science and/or software engineering background. A good understanding of data engineering principles is important as you will often be responsible for creating your own data models or working with data engineering to optimize internal team frameworks and services. A love for testing, validation and configuration as code will set you apart. You are not required to be an expert in one field, rather, your ability to learn and problem solve is much more desirable. Additionally, the ability to partner and share your expertise with others will help you succeed.
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