The company is looking to improve product development and commercialization efforts by analyzing and synthesizing product feedback from various sources.
Requirements
- 4 years of experience in statistical problem-solving and analyzing data sets using SQL or comparable coding.
- 3 years of experience with designing experiments, developing statistical models, measurement, and identifying business opportunities (preferred).
- Experience with Java or Python (required).
- Experience with statistical methods and data modeling (required).
- Experience with machine learning techniques (preferred).
- Experience with data visualization tools (required).
Responsibilities
- Design and implement data processes using Java or Python to collect, clean, transform, and analyze product feedback data from various sources.
- Conduct advanced quantitative data analysis using SQL and statistical methods to identify significant trends, correlations, and root causes within product feedback.
- Develop sophisticated data models and visualizations to communicate complex feedback insights in a clear and compelling manner to technical and non-technical audiences.
- Collaborate with data scientists to apply statistical and potentially machine learning techniques to uncover deeper patterns and predict future user needs based on feedback.
- Build and maintain dashboards and reporting tools that enable stakeholders to self-serve and monitor key product feedback metrics.
Other
- Bachelor's degree in Engineering, Mathematics, Quantitative Science, or related technical fields, or equivalent practical experience.
- 4 years of experience working in data analytics, consulting, data science, engineering, or a technical operations role.
- Master's degree in a quantitative field (e.g., Statistics, Computer Science, Engineering, Mathematics, Data Science, etc.) (preferred).
- Ability to work with stakeholders to develop a deep understanding of user needs and pain points.
