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Description
APPLE INC has the following available in Austin, Texas. Engage with business teams to find opportunities, understand requirements, and translate those requirements into technical solutions. Develop a predictive model aimed at minimizing instances of abusive refunds. Provide assistance to partner teams in the rollout of new features. Design data science approach, implement workflows within a Spark environment, and integrate big data and machine learning models, applying tried-and-true techniques. Combat spikes in refund abuse using analytical tools. Oversee and enhance the performance of models. Develop custom algorithms: develop a specialized algorithm leveraging extensive expertise in refund abuse and software engineering. Working closely with the labeling team, craft a precise machine learning solution aimed at mitigating financial losses for Apple. 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. Detect numerous fraudulent refund trends originating from a vast array of fake accounts. Promptly respond to these findings, adapting model to effectively block those abusive refund requests. Communicate results of analyses to business partners and executives. Research new technologies and methods across data science, data engineering, and data visualization to improve the technical capabilities of the team. 40 hours/week.
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Minimum Qualifications
- Master's degree or foreign equivalent in Data Science or related field.
- Experience and/or education must include:
- Designing data science approach, and developing custom algorithms to address business problems using Python, SQL, Spark, and Machine Learning.
- Applying practical experience with and theoretical understanding of algorithms for classification, regression, clustering, and anomaly detection using Python, SQL, Spark, and Machine Learning.
- Extracting business insights from data and identifying the stories behind the patterns using data analysis skills and tools like PySpark, SQL and Tableau.
- Distilling complex analysis and concepts into concise business-focused takeaways using data analytics skills and tools like Keynote and SQL.
- Engineering novel features and signals, and pushing beyond current tools and approaches using software engineering skills and machine learning knowledge.
- Deploying machine learning solutions to answer real-world questions.
- Implementing data science-related applications in a programming language such as Python, Scala, or Java.
- Theoretical understanding of machine learning algorithms and their relative strengths and weaknesses.
- Using a querying language such as SQL to extract insights from data.
Preferred Qualifications
- N/A
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote 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 .
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