H-1B Job Board

Finding companies that sponsor visas is a lot of work.
We've made your life easier by compiling top companies and startups that hire foreign nationals.

Software Engineer - Data Science, Apple Services Engineering

Apple

Apple

Software Engineering, Data Science
Cupertino, CA, USA
Posted on Wednesday, May 8, 2024

Summary

Posted:
Weekly Hours: 40
Role Number:200549828
We invite outstanding data scientists to join the Product Data Science team, which is a part of Apple Media Products. Our team works across multiple services performing advanced analysis and building features, powered by machine learning, for AppStore, Apple Music, Apple Podcasts, iTunes Store and related products.

Description

The Products Data Science team sits at the intersection of engineering and various businesses across services which together form Apple Media Products. The team’s charter is to apply advanced analytics to improve our portfolio of applications by understanding our customer’s behaviour and anticipating their needs. Our customers are both individuals who use our apps such as Apple Music and content-providing partners who create content for those apps. Our capabilities power some of the features in the various, customer-facing applications produced by Apple Media Products. In our day-to-day work, we collaborate with geographically distributed and multi-functional collaborators to deliver delightful and innovative customer experiences. We work closely with data-engineers, program managers, product managers and business partners to understand and anticipate our customer’s needs, define and build features, and to measure and communicate results. We then work with web-scale datasets to do data exploration, feature engineering, and machine learning model training and deployment. We are also called upon to develop proprietary algorithms, to evaluate and measure model performance, and work with partners on model adoptions. Technically, this role requires a breadth of knowledge of statistical and machine learning methods. It also requires the creativity to invent and customise the algorithms where required and the ability to collaboratively develop and deploy these advanced analytical products.

Minimum Qualifications

Key Qualifications

  • Proficiency in supervised and unsupervised machine learning models (e.g. GLMs, Dimensionality Reduction)
  • Proficiency in statistics (frequentist or Bayesian)
  • Software development experience using Python, Scala, or other, high-level programming language
  • Demonstrable experience of using novel analysis or methodologies to make impactful contributions, to either a product or academic-research
  • Track record of building data science solutions
  • Some experience in data processing / modelling using Spark
  • Familiarity with distributed data platforms
  • Working knowledge of data science production process (unit tests, data pipelines, etc.)
  • Enthusiastic, customer-obsessed team-player who enjoys collaborating in a collegiate environment to build delightful products
  • Initiative and ability to manage projects to completion
  • Managing globally-distributed collaborators through clear and concise communication
  • Communicating technical concepts to non-technical audiences

Preferred Qualifications

Education & Experience

MS/PhD in Statistics, Computer Science, or other quantitative disciplines. Equivalent backgrounds with relevant experience will also be considered.

Additional Requirements

  • We acknowledge the novelty of the data scientist’s role in the analytical world and actively encourage the team to explore and learn. It is desirable to be self-motivated when it comes to keeping abreast of academic innovation in the field. As a part of the team, you will be encouraged to participate in both internal and external conferences, and workshops.

Pay & Benefits

  • Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.