AMP Fraud Data Analyst

Imagine what you can do here. Apple is a place where extraordinary people gather to do their lives best work. Together we create products and experiences people once couldn't have imagined, and now, can't imagine living without. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do.

Description APPLE INC has the following available in Austin, Texas. Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software. Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets. Identify and action upon fraud within the Apple Media Product Store. Work on data wrangling and analytics applications using SQL, Python. Develop long term analysis to drive new and existing fraud programs using Python and statistical analysis. Create re-occurring reports to monitor fraud performance. Create KPI metrics reports on Tableau with historical data as well as on Splunk with real-time data. Formulate data visualization for business stakeholders using data science techniques and Tableau. Lead technical integrations with adjacent analytical teams. Work with cross-functional teams on creating reports/analysis required for new projects using data wrangling techniques and SQL. Draft fraud rule recommendation for fraud models. Investigate fraud attacks to identify root cause of fraud within the Apple Media Products using Python, PySpark and statistical analysis. Consult on fraud risk/exposure for business programs with cross-functional teams as well as outside developers/acquirers(Visa, MasterCard, etc). International Travel Required 5%. 40 hours/week.

Minimum Qualifications

• Master's degree or foreign equivalent in Information Technology and Management, Information Technology, Computer Science or related field.
• Experience and/or education must include:
• Create visualization dashboards in Tableau.
• Python notebooks to perform analysis.
• Use Hadoop to perform analysis.
• Using SQL to query on structured or unstructured data.
• Use Data Science to structure models and analyze data.
• Use statistical analysis to improve models.
• Data Wrangling, data munging or data remediation.

Preferred Qualifications

• N/A

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