Job Summary
The primary objective of this role is to design and implement predictive and statistical models that utilize extensive hardware and software telemetry data to evaluate fleet health, reliability, and overall performance. This position involves converting detailed analyses into high-level visual presentations and actionable insights by working closely with various teams, including product, engineering, hardware, software, and support.
Responsibilities
- Develop predictive and statistical models to evaluate fleet performance and reliability.
- Utilize telemetry data from large-scale hardware and software systems.
- Transform thorough analyses into visualizations that can be presented to executives.
- Collaborate effectively with interdisciplinary teams to derive actionable recommendations.
Qualifications
- Master’s degree or Ph.D. in a quantitative field is required.
- 5 to 8+ years of experience in machine learning, statistical modeling, and quantitative research.
- Proficient in Python and SQL with a solid grasp of major machine learning and statistics libraries.
- Demonstrated experience in research, including experimental design, and a history of publications, presentations, or patents.
Everpure provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
