Senior Data Scientist

Role Description

Join Vonage and help us innovate cloud communications for businesses worldwide!

As a Senior Data Scientist for Verify V2 Data Products, Insights & Monetization, you will:

• Build the quantitative foundation that proves and amplifies Verify v2's value.
• Transform verification telemetry into a reliable, customer-facing data infrastructure that demonstrates measurable ROI.
• Own the end-to-end data pipeline from raw events to customer-visible metrics.

What You'll Own

• Customer Value Infrastructure (Prove ROI at Every Level)
  • Build the metrics that quantify customer-specific business impact.
  • Design and maintain a real-time Customer ROI Engine.
  • Create customer-facing Value Dashboards.
  • Develop attribution models connecting verification outcomes to downstream business metrics.
  • Establish pricing intelligence at the customer level.
• Channel Performance & Optimization (Make Every Verification Smarter)
  • Create a single source of truth for channel economics.
  • Build the intelligence layer for workflow optimization.
• Product Data Platform (Foundation for Autonomy)
  • Design data architecture that enables autonomous decision-making.
  • Build certified, versioned datasets powering self-serve analytics.
  • Implement data quality infrastructure.
  • Ship ML/analytics products that move toward autonomous verification.
• Monetization (Turn Data into Revenue)
  • Develop data products that customers will pay for.
  • Define commercial success.
  • Build the business case for each offering with clear ROI narratives.

Key Responsibilities

• Own the customer value narrative.
• Ship production ML systems.
• Create reliable, self-serve data products.
• Drive pricing and packaging decisions.
• Partner across the organization.
• Report to leadership.

Success Measures

• Customer Value Proof : 100% of enterprise customers have ROI dashboards; X% increase in documented customer savings.
• Channel Optimization : +X% conversion rate improvement; −X seconds median time-to-verify; −X% cost-per-success.
• Fraud & Abuse : −X% fraudulent traffic; $Xm in prevented losses;
• Data Product Revenue : X% attach rate on premium insights; $Xm incremental ARR from data products.
• Platform Readiness : Certified datasets powering ≥3 autonomous routing decisions;

What "Great" Looks Like

• Core Data Science
  • Experimentation design and causal inference.
  • Predictive modeling.
  • Anomaly detection with adversarial thinking.
  • Customer analytics.
• Data Engineering Fluency
  • Strong SQL; Python.
  • Event-driven architecture.
  • Data modeling.
  • MLOps.
• Product & Commercial Analytics
  • Pricing analytics.
  • Funnel analysis.
  • Dashboard design and narrative clarity.
  • Packaging and monetization strategy for data products.
• Domain Expertise (Highly Valued)
  • CPaaS, verification, or 2FA.
  • Silent Authentication.
  • Fraud and risk.
  • Privacy and compliance.

Background

• 5–8+ years in data science/analytics, with ≥2 years building and shipping data products.
• Track record of translating ambiguous business questions into measurable outcomes.
• Experience in B2B SaaS, identity/auth, fintech, messaging/telecom, or fraud analytics preferred.
• Demonstrated ability to influence product and pricing decisions with data.

Why This Role Matters

Verification is shifting from a cost center to a strategic differentiator. The data infrastructure you build will:

• Prove value — Give every customer undeniable evidence of ROI.
• Optimize economics — Make every verification faster, cheaper, and more reliable.
• Enable autonomy — Lay the foundation for a platform that routes, optimizes, and protects without human intervention.