Finance Machine Learning Engineer
Austin, Texas, United States
Machine Learning and AI
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.
Minimum Qualifications
- 5+ Years of relevant experience
- Bachelor's in Computer Science or other related quantitative field
Key Qualifications
Preferred Qualifications
- Efficient python (or equivalent scripting language) programmer experience
- Effective writing SQL in data warehouse and cloud environments
- Experience with the ML ops lifecycle – specifically as it relates to automated deployment, testing, concept drift monitoring and proactive model maintenance
- Practical experience applying, and theoretical understanding of machine learning algorithms and statistical methods for regression, classification, and outlier detection
- Foundational knowledge of efficient data models for analytics and the ability to build batch type, orchestrated data integrations
- Understanding of data validations and automated monitoring to ensure integrity and consistency in data pipelines
- Previous accounting experience or experience working in a corporate finance or accounting organization is a plus.
- Understanding of or ability to learn high level accounting principles, SOX and tax compliance and month-end close process is a plus.
Education & Experience
Additional Requirements
Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.