The company is looking to improve customer engagement and long-term retention by analyzing customer behavior and product adoption.
Requirements
- Strong experience with SQL and Python (or R) for data analysis and modeling
- Proficiency in A/B testing methodologies, causal inference, and predictive modeling
- Familiarity with BI tools (e.g., Tableau, Looker) and data visualization best practices
- Experience with product analytics tools (e.g., Amplitude, StatSig)
- Strong problem-solving skills and the ability to work in a fast-paced, cross-functional environment
- Experience working in B2B SaaS or fintech
Responsibilities
- Develop and apply data-driven methodologies to analyze customer behavior, retention trends, and product adoption
- Design and implement predictive models, causal inference methods, as well as experimentation strategies to measure and optimize the effect of product changes on customer growth and engagement
- Partner with Product, Engineering, and Customer Success teams to identify key opportunities for improving customer engagement and long-term retention
- Collaborate with Data Engineering to build scalable data pipelines that support product analytics and reporting
- Clearly communicate findings and strategic recommendations to both technical and non-technical stakeholders
Other
- Master’s degree or Ph.D. in Statistics, Computer Science, Economics, or a related quantitative field
- 3+ years of experience in a data science, analytics, or related role focused on product analytics
- Ability to translate complex data insights into strategic business recommendations
- Willingness to work in office at least 2 days per week on Wednesday and Thursday
- Ability to work remotely for up to 4 weeks per year
