Data Scientist

Summary

Posted: Nov 6, 2019

Weekly Hours: 40

Role Number: 200113033

Imagine what you could do here. At Apple, new ideas have a way of becoming phenomenal products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Are you in love with data? Do you love deciphering obscure statistics and translating those findings into business actions? If so, we would love to have you in AppleCare! We are looking for someone that will go beyond helping us discover the information hidden in vast amounts of data. The ideal candidate can simplify complex information and translate it into actionable recommendations that help business stakeholders make smarter decisions.

Key Qualifications

  • 5+ years analyzing data and reporting
  • Data and feature engineering in big data systems
  • Deployment / production of models and performance management
  • High-level programming language for analysis (e.g. Python, R)
  • Advanced SQL
  • Mathematical understanding of machine learning techniques such as regression, time series analysis, clustering, decision tree techniques
  • Recent experience with building models such as forecasting growth, predicting churn, customer clustering and anomaly detection
  • Spark, Hadoop or other distributed frameworks


Description

Your primary focus will encompass two areas, applying data science techniques and advanced statistical analysis. 1. End-to-end data science projects In this role, we are looking for someone with hands on experience leading projects throughout the end-to-end modeling workflow. From raw data to feature engineering, to model training, deployment, and long-term performance management, you'll be asked to lead data science projects such as: • Automating scoring using machine learning techniques • Building system for automated fraud detection • Building recommendation systems 2. ADVANCED STATISTICAL ANALYSIS Our team is responsible for analyzing the survey data we collect. You'll be responsible for supporting the team when advanced statistical techniques are required.

Education & Experience

- BA/BS/BE in a quantitative field (Statistics, Computer Science, Ops Research etc.) - Masters or PhD in Statistics/Mathematics is a plus

Additional Requirements

  • - Tableau
  • - Strong project management skills and attention to detail
  • - Strong communication skills
  • - Teradata



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