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Job Description & How to Apply Below
We’re looking for an AI & Business Intelligence Lead to transform how we use data across the company.
This is not a traditional Data Analyst role.
We want someone who is exceptional with AI — particularly Claude — and knows how to combine AI, data, dashboards, automation and business thinking to give leadership a real-time understanding of what is happening across the company.
You’ll take data that currently lives across spreadsheets, marketing platforms, e-commerce systems, finance, CRM, operations and other tools and turn it into live dashboards, automated reporting and actionable business intelligence.
The ultimate goal is simple:
At any moment, leadership should be able to understand:
What happened?
Why did it happen?
What needs our attention?
What should we do next?
What You'll Do
Build our company-wide intelligence system
Create a centralized reporting ecosystem covering areas including:
Revenue & profitability
Marketing performance
CAC, ROAS, MER and LTV
Conversion funnels
Landing page performance
Customer acquisition
Retention & subscriptions
Sales
Finance
Customer experience
Operations
Inventory
Product performance
You'll work with leadership and individual departments to determine the KPIs that actually matter and how they should be measured.
Build live dashboards
Turn fragmented data into clear, easy-to-understand dashboards using tools such as:
Google Looker Studio
Google Sheets / Excel
AI-generated dashboards and artifacts
Internal web dashboards
BI and visualization platforms
You should know how to take something currently being tracked manually in five different spreadsheets and turn it into one reliable source of truth.
Use AI to build faster
You should be highly proficient with Claude and modern AI tools.
We want someone who uses AI every day to:
Build dashboards and internal tools
Analyze large datasets
Write and debug code
Create reporting workflows
Generate SQL
Connect data sources
Automate repetitive analysis
Identify anomalies and trends
Generate executive summaries
Prototype new internal applications
If you still approach every analytics problem the same way you did before generative AI, this probably isn't the right role.
Connect our data
You'll help automate the movement of data between systems.
Depending on the project, that could mean working with:
APIs
SQL
Google Sheets
Excel
Databases
Webhooks
Data connectors
ETL tools
E-commerce platforms
Advertising platforms
CRM systems
Finance systems
You don't necessarily need to be a full-time Data Engineer, but you should be technical enough to figure out how to get data from Point A to Point B reliably.
Turn data into decisions
Building dashboards is only half the job.
We want someone who can interpret what the data is telling us.
Instead of simply reporting:
"Conversion rate decreased from 4.2% to 3.6%."
We want you to investigate why .
Was it traffic quality?
A specific advertising channel?
A new landing page?
Mobile conversion?
Checkout abandonment?
A pricing change?
A particular country?
Then communicate the answer clearly to leadership.
Build AI-powered executive reporting
We want to eventually automate much of our company reporting.
For example, leadership should receive a weekly report explaining:
WHAT HAPPENED
The biggest changes across the business.
WHY IT HAPPENED
The drivers behind those changes.
WHAT NEEDS ATTENTION
Anomalies, risks and opportunities.
WHAT WE SHOULD DO
Specific recommended actions based on the data.
Your job will be to help build the data infrastructure and AI workflows that make this possible.
What We're Looking For
You are probably someone who sits somewhere between:
Business Intelligence + Data Analytics + AI + Automation + Business Strategy.
You should be strong in several of the following:
Claude / Claude Code
Advanced AI prompting and workflows
Excel
Google Sheets
Looker Studio
SQL
APIs
Data visualization
Dashboard development
Data automation
Business analytics
AI-assisted coding
Python
ETL / data pipelines
But technical skills alone aren't enough.
You need to understand business.
You should be comfortable analyzing metrics like:
CAC, LTV, ROAS, MER, AOV, conversion rate, retention, churn, gross margin, contribution margin, revenue…
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