AI Net Revenue Retention Prediction Developer

Jarvik Solutions

Remote · $130k – $160k / year · Full-time · Posted 4 months ago

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About the role

Net Revenue Retention is the metric that determines whether a SaaS business grows from its existing customer base or shrinks despite acquiring new customers. NRR above 110% means the existing base expands faster than it churns; NRR below 90% means the business is leaking even as sales adds new logos. Predicting NRR at the account level — not just measuring it in aggregate — is how customer success teams allocate attention to protect and expand revenue. Our platform serves customer success teams at 65 B2B SaaS companies. Account-level NRR prediction is the next layer of intelligence we're adding: not just 'is this account healthy or at risk' but 'what is the probability distribution of this account's ARR in 12 months, including both churn, downgrade, and expansion scenarios.' You'll lead this capability: designing models that generate account-level ARR trajectory predictions with explicit expansion and contraction probability components, building the signal engineering from product usage, support interaction, and commercial relationship data, and integrating predictions into the CSM workflow in a form that drives specific intervention actions rather than generic alerts.

Fully remote.

Responsibilities

Design account-level ARR trajectory models generating 12-month expansion and contraction probability distributions
Engineer signals from product usage, support patterns, commercial milestones, and executive engagement data
Implement joint modeling of churn, downgrade, and upsell probabilities as competing outcomes
Build prediction integration into CSM workflow surfacing specific intervention recommendations
Develop model explainability showing CSMs which signals most influenced a specific account prediction
Create NRR accuracy tracking comparing predicted ARR trajectories against realized 12-month outcomes

Requirements

6+ years in data science with B2B SaaS customer analytics and NRR or churn modeling experience
Deep understanding of subscription revenue dynamics, expansion motions, and CSM workflow
Strong Python and statistical modeling skills with multi-outcome prediction experience
Experience building ML systems where predictions directly drive operational workflows
Track record improving NRR outcomes through data-driven customer success programs