Singapore, Singapore, Singapore
Operations and Supply Chain
Apple's Analytic Insight team is responsible for mitigating fraud, waste and abuse across Apple. We're looking for an extraordinary data scientist who is passionate about building and maintaining analytical solutions that have direct and measurable impact to Apple. This will be a groundbreaking role that focuses both on gleaning insights from data and the implementation of analytical solutions based on those insights. We're seeking someone that has both a quantitative and technical background in addition to being naturally very curious.
- Ability to provide relevant business insights with data.
- Programming skills in Python
- Experience with SQL, database modeling and data warehousing principles.
- Creativity to go beyond current tools to deliver the best solution to the problem.
- Data visualization experience in Matplotlib, Tableau, ggplot2 or a similar tool.
- Experience with data science algorithms including decision trees, probability networks, association rules, clustering, regression, and neural networks.
- Excellent presentation, communication and social skills, with solid attention to detail.
- Ability to work independently and make key decisions on projects.
- Strong business mindset, possessing an ability to condense complex analysis and technical concepts into clear and concise takeaways for business leaders.
- Ability to comprehensively understand data elements, sources and relationships in business and technical terms.
- Ability to operate appropriately and effectively in a dynamic, highly multi-functional, fast-paced environment.
Build and monitor effective reporting and alerting for fraud and operational health of a line of business. Takes the initiative to develop and automate regular and ad-hoc reports Perform ad-hoc and re-occurring statistical and data science analyses. Work closely with data warehouse architects and software developers to generate flawless business intelligence solutions for end users. Support production analytic solutions. Present results of analyses to business units. Researches, and if applicable, implements new technologies and methods in the areas of data analysis, data visualization and presentation, and data glossaries and libraries.
Education & Experience
M.S. in Computer Science, Mathematics, Economics, Operations Research or related field. OR B.S. in related field with 4+ years experience applying analytical techniques to real business problems.
- Under the hood this one is called “Machine Learning Engineer”