Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research)
OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience
5+ years of experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
3+ years of industry experience with implementing statistical models, machine/deep learning, and analysis (Recommenders, Prediction, Classification, Clustering, etc.) in big data environment.
Preferred Qualifications
Master's Degree in Statistics, Econometrics, Computer Science, Electrical
OR Computer Engineering,
OR related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical
OR Computer Engineering,
OR related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience
Experience with experiments, machine learning, anomaly detection, predictive analysis, exploratory data analysis, and/or other areas of data science on a large-scale product.
Experience with languages like C#/Java is a plus.
Engineering experience using large data systems on SQL, Hadoop, Hive queries, etc.is nice to have.
Responsibilities
Work with partners, product managers and developers to develop & review designs and business requirement.
Apply statistical concepts and techniques to analyze product quality, experiments and user behavior.
Design & develop data transformation processes for petabytes of raw data, perform feature engineering for machine learning.
Develop predictive and prescriptive models using advanced research techniques.
Communicate complex quantitative analysis in a clear, precise, and actionable manner to non-technical audiences.
Collaborate with partners and drive analytic projects end to end.
Adhere to principled data collection practices and policies