Job Requisition ID #26WD97732
Position OverviewWe are seeking a Senior Data Scientist to join our Customer Analytics team within the Customer Success organization. This team plays a critical role in measuring the health of the business and delivering insights that inform strategy, improve decision-making, and drive customer outcomes.
In this role, you will focus on predictive analytics across product usage and the customer lifecycle. You will develop models and insights to better understand user behavior, predict churn and expansion opportunities, and identify strategies to improve product adoption, retention, and overall customer success. You will also bring familiarity with emerging AI techniques to enhance analytical approaches and uncover new value from data. You will collaborate closely with Customer Success, Product, and Go-to-Market teams to translate complex data into clear, actionable recommendations that support business growth and improve the customer experience.
Responsibilities- Analyze product usage data to identify behavioral patterns, segmentation opportunities, and growth drivers
- Develop predictive models to analyze customer churn, retention, expansion, and product adoption
- Build customer health scores and predictive signals to support proactive customer success strategies
- Apply appropriate AI/ML techniques (e.g., advanced segmentation, pattern detection, NLP where relevant) to enhance insights
- Translate business questions into analytical frameworks and data science solutions
- Partner with Customer Success and Product teams to identify opportunities to improve engagement and reduce churn
- Generate actionable insights and recommendations to influence business decisions
- Communicate complex analyses clearly to both technical and non-technical stakeholders
- Collaborate with BI teams to embed predictive insights into dashboards and reporting
Minimum Qualifications- 5-7+ years of experience in Data Science, Advanced Analytics, or similar roles
- Strong proficiency in Python (preferred) or R for data analysis and modeling
- Hands-on experience with predictive modeling techniques (e.g., regression, classification, clustering)
- Strong SQL skills and experience working with large-scale datasets Solid understanding of customer analytics concepts (churn modeling, segmentation, cohort analysis)
- Working knowledge of machine learning/AI techniques and when to apply them to business problems
- Strong analytical thinking and problem-solving skills with a focus on business impact
- Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or related field
Preferred Qualifications - Experience working with product usage / telemetry data
- Experience in SaaS or subscription-based business models
- Familiarity with customer lifecycle metrics (retention, LTV, engagement)
- Exposure to AI applications such as NLP, recommendation systems, or unstructured data analysis
- Experience with data visualization tools (Tableau, Power BI)
- Strong stakeholder management and communication skills
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