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Apple

Machine Learning Engineer - Strategic Data Solutions

Austin, TXPosted 22 days ago

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Why you should apply for a job to Apple:

Ranked as one of the Best Technology Companies in 2020
3.7/5 in overall job satisfaction
3.1/5 in supportive management
66% say women are treated fairly and equally to men
65% would recommend this company to other women
66% say the CEO supports gender diversity

Ratings are based on anonymous reviews by Fairygodboss members. See all reviews ›

Do you love the challenge of solving complex problems that can have a direct and meaningful impact on the company? Do you want to be part of a supportive team that's constantly learning and having fun while solving tough business problems? We'd love to talk to you if you do!

At Apple, new ideas have a way of quickly becoming outstanding products, services, and customer experiences. Bring passion and dedication to your career, and there's no telling what you could accomplish! Strategic Data Solutions empowers internal partners and optimizes the customer experience by delivering data-driven solutions that mitigate fraud, improve security, and optimize efficiency. Our work touches all parts of Apple, from manufacturing to fulfillment to apps and services. The enormous scale and complexity of the problems and our data present exciting opportunities for pushing the limits of existing data science methods.

As an SDS MLE, you will work with teams across Apple, using data analysis and predictive modeling techniques to define, build, deploy, and maintain end-to-end operational solutions that have a direct and measurable impact to the company and our customers.

Our commitment to you: We will provide challenging problems that will engage your curiosity. We will provide an organizational culture that values collaboration, problem-solving, and work-life balance. We will provide mentorship to further develop your technical and leadership skills.

Description
• Engage with stakeholders to translate ambiguous business problems into technical solutions, including finding opportunities, breaking them into solvable segments, defining requirements, assessing level of effort, etc
• Work cooperatively to design data science-driven solutions, balancing the utility of tried-and-true techniques and the benefits of custom solutions
• Collaborate with technical partners to implement robust real-time and batch decisioning in production
• Create reporting and monitor decisioning quality to maintain operational and business metric health
• Investigate trends, assess threat impact, and respond with agile logic changes
• Communicate with stakeholders with varying technical backgrounds and business priorities about your work
• Share what you're learning about novel technologies and methods (in data science, machine learning, data engineering, and software engineering, etc) to improve your team's overall technical capabilities

Preferred Qualifications

Theoretical understanding of machine learning algorithms and their relative strengths and weaknesses

Ability to use a querying language such as SQL to extract insights from data

Demonstrate ability to think holistically about system structures and interactions in order to anticipate technical, business, and customer impact

Effective communication skills to translate complex concepts and analysis into concise, business-focused solutions

Team-oriented skills and values to facilitate effective collaboration with business and technical partners

Minimum Qualifications

Graduate degree with research/work experience utilizing data science techniques (including but not limited to Computer Science, Statistics, Political Science, Biology, etc) or Bachelor's degree with equivalent experience

Practical experience (acquired through work, independent projects, or academic research) in deploying machine learning solutions to answer real-world questions

Practical experience with implementing data science-related applications in a programming language such as Python, Scala, or Java

About Apple

Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.

Size: 10,000+ employees
Industry: Technology: Manufacturing

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