Data Analytics Lead

Description

The company builds infrastructure that lets enterprises create and run AI workforces. Its agents go beyond voice and email: they make decisions, take action, and run operations across whole enterprise systems.

The company was founded through YC-backed, is backed by a16z, Base10, Prysm Capital and Eurazeo, and has raised over $200M. It runs critical operations for global enterprises.

The platform began in logistics and now includes the company's own voice stack, models, and orchestration layer, aimed at enterprises across the real economy.

This role makes data central to how the team builds and improves its products. You will work with Product, Engineering, and Machine Learning to measure how changes to models, agents, and features affect real performance, including through A/B tests and analysis of millions of conversations and workflows, and turn the results into clear insights for the product and ML roadmaps.

Responsibilities

• Set and monitor metrics at the product, feature, and agent level.
• Plan, run, and interpret A/B tests on model updates, prompts, agent behavior, workflows, and product features.
• Measure how agent performance moves client results such as task completion, operational efficiency, response quality, and automation rate.
• Link offline model evaluations to production performance and real customer impact.
• Run deep analyses of conversations, workflows, and product usage to find opportunities and explain performance gaps.
• Investigate anomalies and regressions, find root causes, and recommend fixes.
• Build statistical models, simulations, and analytical frameworks that inform product and ML decisions.
• Work with Engineering to improve instrumentation, data quality, experimentation systems, and analytical data models.
• Build dashboards and self-serve tools so teams can see how products and agents perform.
• Explain findings and recommendations to both technical and non-technical audiences.

Requirements

• You have 4+ years of experience in data science, product analytics, or another highly quantitative product role.
• You have strong experience with experimental design, A/B testing, statistics, causal inference, and hypothesis-driven analysis.
• You are advanced in SQL and Python.
• You have defined and operationalized product and feature metrics.
• You turn ambiguous product questions into rigorous analysis and actionable recommendations.
• You have strong product instincts and can tell statistical significance apart from meaningful product or customer impact.
• You have worked closely with Product, Engineering, or Machine Learning teams.
• You communicate clearly in writing and speaking.
• You pay close attention to detail and care about analytical accuracy.
• You work with founder-level ownership: independent, curious, and willing to go deep.
• You have experience with large language models, AI agents, generative AI, or other probabilistic ML products.
• You have measured the production impact of model, prompt, retrieval, or orchestration changes.
• You understand ML evaluation systems and how offline evaluations relate to online metrics.
• You have analyzed conversational, NLP, speech, or other unstructured data.
• You have experience with enterprise or B2B products.
• You have combined quantitative analysis with qualitative methods such as conversation reviews, customer feedback, surveys, or user research.
• You are familiar with modern analytics infrastructure, data warehouses, experimentation platforms, and business intelligence tools.
• You have worked in a fast-growing startup or another highly ambiguous environment.

Conditions

Applicant data is handled under GDPR and deleted after three months of inactivity.

Benefits

• You will work alongside a top-tier team of engineers and builders.
• You own projects with real autonomy and are encouraged to ship quickly.
• Healthcare, dental, and vision coverage is included.
• Pay is competitive, and equity is part of the package at a high-growth startup.