Job Information
Apple QBA - SDS in Austin, Texas
QBA - SDS
Austin,Texas,United States
Operations and Supply Chain
Apple’s Strategic Data Solutions (SDS) team designs and implements data science and machine learning algorithms that drive strategic impact across Apple to mitigate fraud losses, optimize various business processes, and improve the customer journey across our programs. Our team applies data science and machine learning to drive strategic impact across multiple lines of business at Apple. We are looking for an outstanding analyst who is interested in working closely with AppleCare partner teams; understanding their processes and analytic needs; and developing technical solutions along the way. They will sit side-by-side with our machine learning engineers and analyze complex business problems, have access to internal and external data sources, and be expected to communicate relevant insights to senior leadership and key decision-makers. The ideal candidate works well in collaborative environments with minimal formal structure and is comfortable in changing environments with competing priorities. They must possess solid business acumen, a strong quantitative / technical background, natural curiosity, and the ability to effectively shift between communications styles based on the audience (technical peer review through leadership update).
Description
• Support discovery of business problems • Analyze and interoperate new sources of data • Retrain existing machine learning models • Manage and modify operational thresholds of machine learning models • Perform ad-hoc and reoccurring statistical analyses • Work with data warehouse architects and software developers to generate seamless business intelligence solutions for business partners • Present results of analyses to business units
Minimum Qualifications
BS / MS in technical field (math, statistics, engineering, computer science, analytics, or similar)
At least 3-5 yrs experience working as a data/business analyst, auditor, or related role
Experience applying analytical techniques to provide solutions to real business problems
Experience eliciting business requirements and executive metrics
Experience building business cases and project plans
Experience coordinating with partners to ensure timely project delivery
Key Qualifications
Preferred Qualifications
Programming skills in Python
Background in Fraud Prevention or AppleCare Operations
Strong interpersonal skills with ability to connect and develop strong partnerships
Data visualization
Competent with SQL and big data systems and tools
Strong verbal / written communication skills
Creativity to go beyond current tools to deliver best solution to the problem
Inquisitiveness and a desire for continued self-improvement and development of new skills
Comfort working independently and making key decisions on projects
Ability to tell meaningful and accurate stories with data and visualization
Ability to bridge between ML engineering and business teams to answer questions related to significance of a data pattern, or identifying
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. (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf)
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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 (Opens in a new window) .
Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation or that of other applicants. United States Department of Labor. Learn more (Opens in a new window) .
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