Watch Product Quality- Data
Santa Clara Valley (Cupertino), California, United States
Operations and Supply Chain
Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The people here at Apple don’t just build products — they create the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it! Watch Product Quality is seeking an outstanding data scientist who is passionate about identifying, crafting, and developing data mining solutions that will have a direct impact on product quality. This individual will leverage a tremendous amount of data, both from the supply chain and from customer feedback, to explore strategic areas for pattern detection, anomaly detection, and predictive modeling. The overarching goal will be to identify issues early and provide perspective on how to resolve them. Collaboration with our partners across Operations, Engineering, and AppleCare will be essential. The role requires not only a great foundation in data mining techniques, scripting, and databases, but also an understanding of operations and quality methods. Strong technical, presentation, and organizational skills are critical.
- 5+ years of experience in a Data Science role in the areas of data mining, statistics, machine learning, or related fields. Experience crafting, conducting, analyzing, and interpreting experiments and investigations. Experience in Operations or Consumer Electronics a plus.
- Ability to translate data insights into a clear and compelling narrative with practical outcomes. Outstanding verbal and written communication skills.
- Works well with a team. Able to build relationships and lead by influence. This role requires advocating for change with various teams across Apple.
- Experience articulating and translating business questions and using analytics and data science techniques to answer those questions.
- Experience partnering with internal teams to drive results and providing expertise and direction on analytics, data science, experimental design, and measurement.
- Expertise in statistical data analysis such as linear models, multivariate analysis, sampling methods, and causal inference.
- Experience with common data science toolkits, such as R/Python and various data processing and Machine Learning libraries. Experience with R, Matlab, and variety of programming languages is valuable.
- Experience using query languages such as SQL. Skilled at database design and development.
- Experience in producing powerful visualizations and dashboards that balance both art and science (using Tableau/D3, etc).
- Laser-focused on the smallest details and able to use data forensics to solve complex manufacturing assembly quality issues.
- Experience partnering with contract manufacturers in high-volume production; experience traveling to manufacturing sites.
- Obsessively passionate and inquisitive; seeks to pursue everyday problems in innovative ways.
- Work with internal partners and cross-functional teams to define and refine business and research questions. Use a variety of analysis techniques to address those questions. - Conduct end-to-end analysis across key factory and customer touch points. Leverage data from large and complex datasets, and drive analysis using advanced methods. - Identify key design and manufacturing variables that impact operations performance and the customer experience. Work closely with Operations, Engineering, and AppleCare teams to contribute to root cause investigations and corrective actions. - Develop extensive knowledge of existing metrics. Build new metrics for performance measurement and advocate for changes to existing metrics where needed. - Lead data science and analytics projects throughout product lifecycle. - Partner with data science peers across Apple to build and prototype data pipelines and analysis methods to drive insights at scale. - Evangelize adoption of best practices and build greater awareness of the value of data analytics. - Succinctly communicate updates to the executive team.
Education & Experience
Bachelor’s degree in relevant field, such as Data Science, Machine Learning, Statistics, or Operations Research, or equivalent work experience. Advanced degree (MS, PhD, or MBA) is a plus.