The first step is a feasibility study and development project to establish the initial churn prediction and prevention capability. Rather than jumping directly into complex machine learning, the customer wants to start with a simple, explainable churn index that Customer Success and Sales teams can immediately use to prioritize accounts.
Over time, this index will be expanded with more data sources, segmentation, and predictive power — ultimately evolving into an automated Churn Prevention system supporting the company’s product-led growth (PLG) strategy.
Scope of this assignment:
Design and build the first explainable churn index, leveraging:
- License utilization metrics
- Key transactions and product usage signals
- Adoption breadth across users and features
- Commercial stability indicators
What We’re Looking For:
We are seeking an experienced Data Scientist / Customer Analytics Professional with:
- Strong background in customer analytics and churn modeling
- Proven ability to design explainable, business-friendly metrics and indices
- Experience working with SaaS business models and subscription KPIs
- Skills to balance quick business impact with a roadmap towards predictive and automated solutions
Deliverables:
- Feasibility study and data assessment
- Design and development of the initial churn index
- Clear documentation and recommendations for next phases (towards predictive churn prevention)