Job Description

Locations

• Cupertino, California, United States 95014
• San Diego, California, United States 92128
• Seattle, Washington, United States 98117

Salary

Skills Required

• forward-thinkingintermediate
• creative thinkingintermediate
• hard workintermediate
• analytical skillsintermediate
• instrumentation skillsintermediate
• measurement skillsintermediate
• problem solvingintermediate
• quantitative skillsintermediate
• critical thinking skillsintermediate

Required Qualifications

• 5+ years of industry experience supervising analytics measurement and implementation efforts with hands-on event tagging and code validation. (experience, 5 years)
• Bachelor’s degree in Computer Science, Electrical Engineering, Information Systems, Analytics fields, or a related subject area, or we may consider an equivalent industry experience. (experience)
• 3+ years experience coding in Python and SQL. (experience, 3 years)
• 3+ years experience coding in Hadoop: MapReduce, Hive or Spark SQL. (experience, 3 years)
• 3+ years experience leading the implementation of data collection & data processing efforts from start to finish. (experience, 3 years)
• Previously have been a core member of instrumentation & measurement standards functions. (experience)
• Self-motivation and a can-do attitude. (experience)
• Excellent presentation and communication skills, with strong attention to detail. (experience)

Preferred Qualifications

• Passion for photography or image editing. (experience)
• Objective C to debug code (experience)
• Experience in mobile native apps, specifically tracking & measurement tactics and product development. (experience)
• Master’s degree in CS, EE, Information Systems, Analytics fields, or a related subject area. (degree in cs)

Responsibilities

• Faced with a variety of problems to solve, this role requires strong analytical and quantitative skills. Creativity and critical thinking skills will be put to good use, deconstructing problems and transforming your insights into data backed recommendations.
• 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 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.
• Strong product measurement experience, including app instrumentation, data analysis and agile development standard methodologies.
• Ability to manage large sets of unstructured app behavioral data in a distributed data environment, specifically supervising validation, data post processing business rules, data cleansing, and metrics reporting.

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