5,702 jobs for "Data Architect"

Machine Learning Engineer - Strategic Data Solutions

At Apple - Austin

Posted on Oct 19

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Machine Learning Engineer - Strategic Data Solutions (Retail Fraud)

At Apple

Posted on Oct 16

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Machine Learning Engineer - Strategic Data Solutions (Retail Fraud)

At Apple

Posted on Oct 16

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Machine Learning Engineer - Strategic Data Solutions (Retail Fraud)

At Apple

Posted on Oct 15

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Machine Learning Engineer - Strategic Data Solutions (Retail Fraud)

At Apple

Posted on Oct 15

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Places Data and ML Director

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At JPMorgan Chase - Jersey City

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Sr Lead Software Engineer - UAT Data Platform & Governance Lead

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Posted on Aug 21

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Cyber Data Protection Manager

At Deloitte - Atlanta · Austin

Posted on Aug 21

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AI Project Manager (Data Strategy) - AI Data Service and Operation (Safety Model Operations)

At TikTok

Posted on Oct 28

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Data Scientist - Agentic AI

At Kyndryl - Madrid · Barcelona

Posted on Nov 4

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Technical Program Manager, Data

At Oscar Health - New York

Posted on Oct 29

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Senior Principal Software Engineer, Cloud Architecture

At CarGurus - Boston

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Apple

Machine Learning Engineer - Strategic Data Solutions

Austin, TXPosted 20 days ago

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Imagine what you could do here. At Apple, new ideas have a way of becoming outstanding products, services, and customer experiences very quickly. Bring passion and dedication to your job, and there's no telling what you could accomplish.

Apple's Strategic Data Solutions (SDS) team is looking for a hardworking individual who is passionate about crafting, implementing, and operating analytical solutions that have a direct and measurable impact on Apple and its customers.

As an SDS Machine Learning Engineer, you will employ predictive modeling and statistical analyses to build end-to-end solutions for improving security, fraud prevention, and operational efficiency across the company, from manufacturing to fulfillment to apps and services.

Apple's dedication to customer privacy, the adversarial nature of fraud, and the enormous scale of the business present exciting challenges to traditional machine learning and data science techniques. On this team, we will push the limits of existing data science methods while delivering tangible business value!

Description

Engage with business teams to find opportunities, understand requirements, and translate those requirements into technical solutions.

Design a data science approach, applying tried-and-true techniques or developing custom algorithms as needed for the business problem.

Collaborate with data engineers and platform architects to implement robust production real-time and batch decisioning solutions.

Ensure operational and business metric health by monitoring production decision points.

Investigate adversarial trends, identify behavior patterns, and respond with agile logic changes.

Communicate results of analyses to business partners and executives.

Preferred Qualifications

Ability to comprehend and debug complex systems integrations spanning toolchains and teams.

Ability to extract meaningful business insights from data and identify the stories behind the patterns.

Excellent presentation skills, distilling complex analysis and concepts into concise business-focused takeaways.

Creativity to engineer novel features and signals, and to push beyond current tools and approaches.

Experience working with images, training and deploying CNN models in production environments, and using Computer Vision techniques.

Minimum Qualifications

Education in a quantitative field, such as Computer Science, Applied Mathematics, or Statistics, or equivalent professional experience.

Practical experience with and theoretical understanding of algorithms for classification, regression, clustering, and anomaly detection.

Working knowledge of relational databases, including SQL, and large-scale distributed systems such as Hadoop and Spark.

Ability to implement data science pipelines and applications in a general 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

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