Data Scientist, Testing and Optimization - Cupertino
Santa Clara Valley (Cupertino), California, United States
Software and Services
We are looking for a results-oriented seasoned data scientist to join our team and craft the future of Apple Pay. You are analytically skilled and have strong business acumen. You will be a thought partner to the product and business teams, understand their goals and then build, test, implement and analyze various experimental designs. Our culture is about getting things done iteratively and rapidly, with open feedback and debate along the way; we believe analytics is a team sport, but we strive for independent decision-making and taking smart risks.
- Expert knowledge of experimental design principles with 3+yrs of demonstrated hands on experience creating and running A/B or multivariate testing projects
- Well versed with and have experience applying various statistical methodologies including Bayesian and non-parametric techniques, hypothesis testing, ANOVA, Regression, fixed and random effects etc. to measure the impact of experiments
- Hands on experience working in big data environments such as Hadoop, Apache Spark and using Python / SQL or comparable languages for manipulating and analyzing complex clickstream data
- Prior experience working with A/B testing platforms like Adobe Target or Optimizely is desirable. Familiarity with tools such as Tableau and Jupyter notebooks are preferred
- Excellent written and verbal communication skills.
Collaborate with product teams to propose, develop and implement experiments for investigating and answering business questions Partner with Engineering and QA team to build A/B and Multivariate tests using proprietary in-house tools. Partner with Data Engineering to ensure accurate capture of experiment values into the analytical clickstream. Quantify and analyze testing outcomes and provide analytical readouts on test results using various statistical techniques. Continuously track the business and technical requirements of the experimentation system; improve testing processes continuously to meet business needs. Make recommendations to systems development teams for system improvements.
Education & Experience
B.S. in Computer Sciences, Quantitative Methods or Statistics with 5+ years experience applying statistical and/or data mining techniques to real business problems using the required technical skills. Preferred - M.S. in Statistics, Operations Research, Applied Social Sciences or related field with 3+ years of relevant experience.