Senior Data Scientist, Input Experience
Santa Clara Valley (Cupertino) , California , United States
Software and Services
Posted: Mar 26, 2021
Weekly Hours: 40
Role Number: 200232631
At Apple, our goal is to provide an effortless input experience to everyone, no matter what languages they speak, across modalities, with world-class intelligence at the core. The Input Experience organization is directly responsible for keyboard and pencil input across multiple platforms. We also work very closely with the Siri speech team to seamlessly integrate dictation into our user's text input. We are looking for an experienced Data Scientist to help us develop insights into how Apple customers experience our input technologies. This includes but is not limited to: - Accuracy of our intelligent algorithms such as autocorrection and QuickPath. - Usage of specific features including engagement - Soft spots in our technology stack that might contribute to user frustration These insights will be developed via a combination of metrics, A/B testing, user studies/surveys and other data-oriented approaches.
- Foundation in data science, machine learning, and analytics, including statistical data analysis and A/B testing.
- 5+ years of proven experience building data science driven solutions to solve business problems.
- Ability to dive into into the details on product features and underlying architecture in order to help define success criteria and the ways we can measure that via metrics and other approaches. This will involve close collaboration with the engineering teams that develop those features.
- Conceive and design end-to-end optimized data modeling pipelines and customer analytic scripted solutions using Python and/or Spark.
- Strong programming skills, including data-querying skills (SQL and/or Spark, etc.) and experience with a scripting language for data processing and development (e.g., Python, R, or Scala).
- Solid experience working with Tableau or other data visualization technologies.
- Ability to work cross-functionally with other Apple organizations including Marketing, Data Analytics, User Studies, Siri and application development teams.
- Strong communication skills and the ability to naturally explain difficult technical topics to everyone from data scientists to engineers to business partners and leaders.
- Experience/interest in working across different global cultures and languages. Knowledge of other languages (e.g, Chinese, Japanese, Arabic) is a plus!
The Input Experience organization is looking for an experienced and highly motivated data scientist! You will partner across engineering groups building world class intelligent input, and evangelize a culture of using data to measure, understand, and improve our products and features. You have a background that fuses data science, engineering, and product thinking. You have years of practical experience building measurement, evaluation, and insights to improve products. IN THIS ROLE, YOU WILL: - Work closely with leadership and engineering teams to help define and prioritize the insights we need to make the very best products - Drive the generation of insights from raw, unstructured data to improve existing features and explore future directions. Develop extensive knowledge of existing metrics, advocating for changes where needed. - Work closely with engineering teams to guarantee the consistency and validity of metrics across platforms, modalities and languages. - Conduct analysis that includes data gathering and requirement specifications, processing, analysis, and report generation. - Drive regular insights reports and presentations with Apple's leadership teams. - Tackle difficult, non-routine analysis problems, applying advanced analytical methods as needed. - Partner with your peers to build and prototype analysis pipelines that provide insights at scale. - Promote adoption of best practices and build greater awareness of common data analysis pitfalls.
Education & Experience
Advanced degree in CS, Data Science, Operational Research, Bioinformatics, Statistics or other quantitative field.