Data Scientist

Stealth Startup; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

Stealth Startup is seeking a Data Scientist to drive research around how consumer LLMs search, reason, and synthesize information. You will design experiments, build data pipelines, and publish findings while collaborating with product and engineering teams.

You will perform causal inference and measurement when traditional A/B testing isn’t possible, stay current on related research, and translate insights into product capabilities.

Qualifications

• Expert-level Python and SQL.
• Strong statistical and experimentation fundamentals.
• Experience with experiment design, effect estimation, and evaluation metrics.
• Comfortable working in early-stage, ambiguous environments.
• Able to balance speed with analytical rigor.
• Strong written and verbal communication.
• Ability to influence stakeholders using evidence.

Responsibilities

• Drive research into consumer LLM search, reasoning, and source synthesis.
• Stay current on AEO/GEO research and develop/test hypotheses.
• Publish research findings.
• Support product and engineering teams with analysis and experimentation.
• Work on agent evaluations and core analytical pipelines.
• Design and analyze experiments.
• Perform causal inference and measurement when traditional A/B testing isn't possible.
• Build data pipelines and recurring measurement systems.
• Turn research findings into product capabilities.

Skills

Python

SQL

Experiment design

Tools

Pandas

NumPy

Job description

We are looking for a Data Scientist to drive research around how consumer LLMs search, reason, and synthesize information.

Responsibilities

• Drive research into consumer LLM search, reasoning, and source synthesis.
• Stay current on AEO/GEO research and develop/test hypotheses.
• Publish research findings.
• Support product and engineering teams with analysis and experimentation.
• Work on agent evaluations and core analytical pipelines.
• Design and analyze experiments.
• Perform causal inference and measurement when traditional A/B testing isn't possible.
• Build data pipelines and recurring measurement systems.
• Turn research findings into product capabilities.

Qualifications

• Expert-level Python and SQL.
• Strong statistical and experimentation fundamentals.
• Experience with experiment design, effect estimation, and evaluation metrics.
• Comfortable working in early-stage, ambiguous environments.
• Able to balance speed with analytical rigor.
• Strong written and verbal communication.
• Ability to influence stakeholders using evidence