Analytics Data Instrumentation Lead

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Company: Apple

Location: Austin, TX 78745

Description:

Summary
We're idealists. Inventors. Forever tinkering with products and processes, always on the lookout for better. Whether you work at our global offices, offsite, or even at home, a job at Apple will be demanding. But it also rewards forward-thinking, creative thinking, and hard work. And none of us here would have it any other way. Does an exciting, dynamic, and fast-paced environment catch your attention? Consider joining our team!

The Creativity Apps team is looking for an hands-on Analytics Instrumentation professional. We'd like to find a thought partner to the engineering and product teams to help understand their goals. We prefer a problem solver with strong instrumentation and measurement skills suited to approach various kinds of challenges in sophisticated environments. Someone able to use analytical skills to develop measurement plans and work with multi-functional teams towards driving client and server Instrumentation.

Description
You will be faced with a variety of problems to solve, and you should be well equipped with strong analytical and quantitative skills to take on these challenges in sophisticated environments. Your creativity and critical thinking skills will be put to good use, deconstructing problems and transforming your insights into data-backed recommendations. In this role, you will perform the following:

Work with large volumes of data; extract and manipulate large datasets using tools such as Spark SQL, command line, and scripting languages.
Analyze data covering a wide range of information from user profile to feature usage behavior signals and identify new engagement patterns through data mining.
Conduct hypothesis-driven exploratory analysis, build feature engineering, design the best structure, and select the most appropriate modeling techniques from a variety of machine learning models to understand feature impact on audience habituation and retention.
Design, develop, validate, and maintain big data-driven predictive models, tools, and pipelines to improve user engagement using the latest technologies in machine learning, user pattern recognition, and data modeling based on user lifecycle events.
Collaborate with product, design, engineering groups to translate a feature & design functionality question to a data science problem and formulate innovative solutions to experiment and implement advanced data mining techniques.
Communicate complex concepts and the results of the analyses in a clear and effective manner to senior management.

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