AI Data Analyst

AI Data Analyst

Location: Remote (US) \| Type: Full Time \| Experience: 0 to 2 years \| Pay: $70K-$95K

About the Role

A deployed AI system is only as trustworthy as the data feeding it. When a number does not reconcile, or an AI app quietly returns the wrong answer, people stop trusting it, fall back to their own spreadsheets, and the whole investment slips away. Your job is to keep that from happening. You own the analytics assets and the data hygiene the AI applications depend on, and you sit close to the teams whose work those numbers describe.

The company is a fully remote insurance and risk-advisory consulting firm where the numbers have to be right and the people producing them have to trust you. This is an early-career role on a clear path: you start as an analyst keeping the data honest and grow into owning the pipelines and models outright.

You do not need to arrive an expert. You need to be curious, rigorous, hard to fool, and genuinely interested in how the business makes money and where the work actually happens.

What You'll Do

• Own the regular analytics and reporting the firm and its AI applications run on, building new views when a team needs them and retiring the ones nobody trusts
• Chase down numbers that look off before anyone else notices, then explain plainly what went wrong
• Hold the line on definitions, so "active client" means one thing across every analytics asset
• Turn a fuzzy question from a team lead into a number people believe, and stay honest about what the data can and cannot say
• Sit with operations, finance, and the client-facing crew to drive adoption of the data layer one person at a time
• Learn the pipelines and warehouse models over your first year and start extending them yourself

Qualifications

• 0 to 2 years working with data, or a strong first move from consulting, professional services, or a customer-facing role
• SQL fluency: comfortable writing queries, joining tables, and reasoning about data. This is the one technical must-have
• A feel for data quality and how messy real data actually gets
• Evidence you have used AI in earnest already, whether that is ChatGPT, Claude, or an automation you built yourself
• Eagerness to learn dbt, warehouse modeling, and how pipelines fit together
• Nice to have:

BI experience in Tableau, Power BI, or Looker; exposure to dbt, Snowflake, BigQuery, or git; a little Python; a consulting or professional-services background

Why Join Us

You walk in as an analyst and, a year or two on, walk out as the person who owns the company's data layer. The path from AI Data Analyst to Analytics Engineer is named on purpose, with a comp step to match as you take on modeling and pipeline ownership.

This is a remote-first firm that would rather grow a high-ceiling person into a scarce role than rent it. The analysts who become great here are the ones who never lose the thread back to the business problem.