Founding Data Scientist

present of AI; San Francisco (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

HappyRobot seeks a data science/product analytics professional to measure how AI agent changes affect client outcomes. You will design experiments, apply statistics, and analyze large volumes of conversation data to tell engineers and business teams what matters.

You should have several years in data science or product analytics, write confident SQL and Python, and handle ambiguity. You’ll define metrics, link lab tests to production results, and translate findings into concrete product

Qualifications

• Several years in data science or product analytics.
• Proficient in SQL and Python.
• Strong statistical knowledge.
• Ability to explain findings to both engineers and non-technical teammates.

Responsibilities

• Measure impact of AI agent changes on client outcomes.
• Design and analyze experiments (A/B tests).
• Interpret results for engineers and non-technical teammates.
• Define product metrics and communicate insights to stakeholders.

Skills

A/B testing

SQL

Python

Statistics

Metrics definition

Conversation analysis

Job description

The role centers on measuring whether changes to AI agents actually help clients, using experiments, solid statistics, and deep dives into large volumes of conversation and workflow data. A strong candidate has several years in data science or product analytics, writes confident SQL and Python, and can tell a statistically significant result from one that matters to a customer. Comfort with ambiguity and the ability to explain findings to both engineers and non-technical teammates matter just as much.

How it fits the AI era

AI agents behave in probabilistic ways, so the same change can help one kind of call and hurt another, and careful measurement becomes a core part of building the product. Data scientists here help decide which model, prompt or workflow changes are truly better, and link lab test results to real results in production. What stays human is choosing which metrics reflect real value, judging the tradeoffs, and turning numbers into decisions the team will act on.

How it builds AI experience

The work gives direct experience evaluating voice and email agents running real operations for enterprise clients, including A/B testing prompts and models and studying millions of conversations. To build this beforehand, practice evaluating an LLM-based tool on a small project, compare offline test scores to outcomes from real usage, and read through transcripts to explain why results differ.

Worth showing

• A/B test design and analysis
• Causal inference and statistics
• SQL and Python depth
• Defining product and agent metrics
• Analyzing conversation or text data

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About HappyRobot

AI voice and email agents that autonomously handle the phone calls and operational busywork of supply chain and enterprise teams.