Business Intelligence Engineer

Job description

DESCRIPTION

You will design and execute ongoing programs of experimentation and study which inform each of these efforts. You will work closely with software engineers to create innovative randomized experiments within the constraints of production software systems. You will seek out hidden and valuable correlations between the easily-measurable and the hard-to-quantify, within immense volumes of real-world data. You will formulate quantitative metrics which allow us to track our progress, and then devise creative measurement and audit solutions which allow us to track those metrics with minimal cost and human effort. You will provide input into business and technical direction, steering broader solutions in support of these objectives. This role is expected to push the boundaries of measurability without sacrificing rigor.

Key responsibilities:
• Work closely with management, software engineering leaders, and business teams to plan catalog data improvements so as to maximize customer improvement impact.
• Triage many possible courses of action in a high-ambiguity environment, making use of both quantitative analysis and business judgment.
• Collaborate with software engineering teams to integrate experimental capabilities into large-scale, highly complex Amazon production systems.
• Report results in a manner which is both statistically rigorous and compellingly relevant.
• Assist in recruiting, mentoring, developing, and training other Research Scientists as well as other technical roles when needed.

Desired profile

BASIC QUALIFICATIONS

Basic Qualifications:
• Master's degree in Mathematics, Statistics, Operations Research, or in a field of experimental science.
• Theory and practice of Design of Experiments and statistical analysis of results.
• Experience using operations research techniques for solution optimization and continuous process improvement.
• Programming skills sufficient to extract, transform, and clean large (multi-TB) data sets in a Unix/Linux environment.
• Proficiency in a statistics package such as SPSS, SAS, S-PLUS, or R.