Our team, part of the Customer Success Engineering org, is fanatically focused on customer love for E+D: quantifying it, deeply understanding it, democratizing it, and improving it. We turn customer satisfaction into a signal as clear and indispensable as usage or perf, develop deep insights on what drives it, and do proactive customer outreaches to increase it. Our team puts some science behind customer love, enabling engineering teams in E+D to better understand their issues. We are a combined engineering and DS team architecting the system that underpins these efforts, including a survey system, the backend storage where we blend in telemetry and other sources, to augment the signal, ML models to pinpoint drivers and find correlations, and our proactive outreach platform that interfaces with support and enables us easily orchestrate campaigns to connect directly with customers in a personal way.
Opportunities and responsibilities include: Being one of the stewards for a key business metric across E+D Working as part of a results-oriented, data-driven team that embraces experimentation Collaborating with engineers, program managers and partner teams to develop insights from our signals Building lasting models for analyzing and understanding satisfaction data.
5 years of experience with machine learning, natural language processing and experiment design Experience applying statistical methods such as hypothesis testing, p-values, confidence intervals, regression, classification, and optimization Development experience in C#/C++/Java/R/Python or similar programming language Strong communications skills, in particular written research results and effective presentations Familiarity with distributed data processing/analysis and modeling paradigms, such as Map-Reduce, is a plus Expertise in survey methodology is a plus BS/BA in computer science, Engineering,