Data Science Manager, Health

Apple | Cupertino, Ca

Date listed

7 months ago

Employment Type

Full time



Total Funding

$6.2 billion

Glassdoor Rating

4/5 (15000 reviews)

Keywords: sql spark python pandas ml

Our ever-evolving suite of Heath and Wellness products for iPhone and Watch are helping our users live more active, healthier lives. Be ready to make something great when you come here. Dynamic, inspiring people and innovative, industry-defining technologies are the norm at Apple. The people who work here have reinvented and defined entire industries with our products and services. The same dedication to innovation also applies to our business practices - strengthening our commitment to leave the world better than we found it.

- Define and share a strategic vision for the function. Lead a talented team with proven data science & analytic skills. Motivate and ensure success for the team by defining roles and responsibilities that are clearly communicated, establish processes, and develop personal development plans. - Contribute to developing strategic and tactical plans for the support of Health projects. All with a focus on supporting customer privacy and control of their data. - You will partner with other leaders across Health to achieve success against complex initiatives. - You will lead, recruit, and guide a team with varied strengths of high-performing data analysts and data scientists focused on diving deep into a complex space. Own and deliver against a prioritized multi-year roadmap across ML, analytics, datasets, reports, and dashboards that takes into account new feature and product launches. - You will Increase internal adoption of advanced analytics methods including machine learning and statistics. - Propose marketing and product changes backed by well-defined experiments and data analytics. - Design and evaluate experiments that help define opportunities for improved product feature effectiveness and greater customer satisfaction. - Analytics, statistical analysis, and visualization of data to help understand our data.

Skills & requirements

  • 10+ years experience on data science, analytics, or reporting teams that support product development. 5+ years leading teams.
  • Excellent communication, collaboration, partner management, and planning skills; proven success building consensus for an innovative and bold vision of how data can improve the user experience.
  • Ability to communicate the results of analyses in a clear and effective manner with product and leadership teams to influence the overall strategy of the product. You should have a shown ability to work with executive level partners and peers across a range of functions.
  • Be able to guide and lead analysis, investigation, and experimentation efforts across teams of data scientists and data analysts.
  • Proven business insight; ability to understand and anticipate the decisions partners can make supported by data.
  • Experience in partnering to create and execute upon a team/group vision. Ability to hire, mentor, and grow the skills of individual contributors in data analysis and data science.
  • Well-rounded individual with the ability to write code to query and transform both unstructured and structured data—acting as a mentor to your team in these areas—while not afraid to dig in and get into the details.
  • Previous programming skills in Python, SQL, or similar and comfort with advanced analytics tools such as Pandas, R, Spark, and Tableau.
  • Experience in advanced quantitative methods and model development with a strong focus in exploratory data science. Experience with regression, classification, clustering, and time-series analyses. Strong understanding of statistical theory and applications.
  • Partner effectively with engineering partners to meet the data needs of the business, translating feature requirements into data science and data engineering requirements.
  • Possess a real passion for innovation and have a knack for seeing around corners

Phd in Statistics, BioInformatics, Physics, Operations Research or similar quantitative domain. Alternatively, a comparable industry career with significant experience in data science.