Lead Product Manager Analytics

About the role

Netomi is hiring a Lead/Senior Product Manager to own the Analytics, Reporting, and Conversational BI product surfaces in Agentic Studio—the measurement and trust layer that helps enterprises build, operate, and continuously improve agentic customer experiences across chat, mobile, email, messaging, and voice/IVR. In mission‑critical environments (airlines, retail, banking, gaming), analytics is not a “dashboard”; it’s the control plane for reliability, governance, and outcomes. You will lead the productization of end-to-end analytics including real-time operational monitoring, historical reporting, LLM quality/evaluation (autoevals), observability for tool calling and workflows, and Conversational BI (natural language exploration over a governed metrics model). This role requires deep domain fluency in data science, data preparation, analytics systems, and the realities of LLM-driven systems (probabilistic outputs, evaluation, safety/guardrails, and runtime tracing)—combined with strong product craft, design sense, and delivery execution. This is an opportunity to lead with data at the frontier: partnering with internal Data Science and Engineering teams while collaborating with frontier model and cloud ecosystem partners to deliver best-in-class analytics and governance for enterprise agentic AI.

Responsibilities

• Define and execute the Analytics/Evals/Governance roadmap with clear sequencing (MVP → v1 → v2) and measurable adoption targets.

• Partner deeply with Data Science to productize evaluation methodology (what we score, how we calibrate, how we prevent “gaming,” how we track drift).

• Partner with Engineering and Observability teams to standardize telemetry (tool spans, workflow transitions, model calls, cost/latency metrics) and make it usable in product.

• Drive a cohesive Agentic Studio UX across Build / Operate / Improve workflows: dashboards, drill-downs, investigation flows, alerts, and remediation actions.

• Establish objective success metrics and instrument them end-to-end (data correctness, timeliness, reliability, and customer impact).

• Work with Delivery/CS and enterprise partners to ensure analytics is usable for real operational processes: incident response, change management, governance reviews, and quarterly business reviews.

Requirements

• Bachelor’s degree in Computer Science, Data Science, Engineering, Statistics, or a related quantitative/technical field (Master’s a plus).

• 6–10+ years of experience across Product Management and/or Data Science/Analytics leadership, including shipping analytics products to enterprise users.

• Demonstrated depth in: data modeling, telemetry/event schemas, ETL/ELT concepts, and analytics correctness.

• Building operational + business reporting (real-time monitoring and historical analytics).

• Experimentation and measurement design (A/B testing concepts, uplift measurement, cohorting).

• Strong hands-on experience applied to AI/LLM or data science platforms, including at least several of:

• LLM evaluation methods (automated scoring, multi-turn evaluation, calibration).

• Observability for probabilistic systems (quality + latency + cost).

• Tool calling / workflow execution analytics and failure taxonomy.

• Governance measurement (policy outcomes, escalation triggers, compliance reporting).

• Strong product craft: UX and information architecture instincts, ability to design operator workflows, and capability packaging that scales across customers.

Preferred Qualification

• Experience building analytics for multi-tenant SaaS and regulated customers (auditability, RBAC, retention controls, privacy-by-design).

• Familiarity with cloud analytics stacks and enterprise BI integration patterns.

• Experience partnering with major cloud and frontier AI vendors (model providers, observability stacks, data platforms) to ship joint capabilities.

• Experience with contact center / CX metrics (containment, resolution, AHT, CSAT, handoff performance) and multi-channel operations (voice + digital).