Senior Data Scientist - Customer Experience
$132,000–$166,000 year
On-siteMountain View Santa Clara County, California, United States
Job Summary
Conduct deep-dive data analysis and diagnostic investigations to diagnose metric shifts and uncover actionable trends in customer behavior. Develop practical predictive models for churn and upsell forecasting to optimize Customer Success workflows, while applying causal inference to evaluate the true business impact of initiatives. Collaborate with cross-functional stakeholders to create data stories that drive customer retention and identify revenue growth opportunities. Self-serve engineering tasks by building foundational data pipelines and dashboards, and assist in establishing Key Performance Indicators for customer success.
Required Qualifications
- Bachelor's degree or higher in a related field, with a focus on data science, statistics, or a related quantitative discipline
- 3-5 years of relevant experience in data science, with a demonstrated ability to conduct deep-dive analyses, diagnose metric shifts, and apply pragmatic modeling techniques to drive business impact
- Proficiency in applied statistics and practical machine learning, with knowledge of causal inference, experimentation (A/B testing), forecasting, and regression
- Advanced proficiency in SQL for complex data extraction and manipulation
- Working knowledge of data pipelining tools (e.g., dbt, Airflow)
- Proficiency in programming languages such as Python for data analysis, automation, and modeling
- Working knowledge of Business Intelligence tools (e.g., Tableau, Sigma), with a strong understanding of best practices for dashboarding and data visualization to communicate insights
- Hands-on experience designing and deploying AI/LLM-based solutions
- Strong communication skills, with the ability to convey complex concepts clearly and effectively to stakeholders
- Strong organizational skills, with the ability to manage multiple projects and deadlines effectively
- A tech-curious mindset with a willingness to learn new technologies and methodologies to stay at the forefront of data science innovation
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