About the Role

Our client is a growing e-commerce agency that helps brands scale on Amazon and other marketplaces. They’re making AI part of how the whole firm works and want someone to lead it. You’ll run their move to a new retail analytics platform, set up how the team uses Claude and other AI tools, build the skills and automations people use every day, and make sure the data underneath can be trusted.

You’ll need to be a hands-on builder, a careful tester, and patient when training non-technical colleagues.

What You’ll Own

AI platform and operating model

- Qore onboarding and automations: Lead the firm’s migration to Qore. Write role-specific SOPs that keep advertising in Xnurta and retail and reporting in Qore. Build and own Qore skills. Any automation that changes a client account must be logged, reversible and approved by leadership.
- AI operating model and rollout: Define which AI tool (Qore, Claude, Gemini) is used for which tasks, and write task-based SOPs. Roll this out in phases with targeted training. Manage Claude Projects and skills, and keep token and context usage efficient to control monthly costs.
- Tool vetting: Test new skills, plugins and connectors in an isolated environment with no client data before anything is deployed. Keep a complete register of approved tools.

Data, reporting and forecasting

- Data foundation: Validate the Trellis data migration by reconciling BigQuery data against the source consoles. Centralize and document data definitions, and run regular quality checks.
- Client reporting: Build Qore dashboards for recurring sales, ad performance and major retail events.



Retire Looker Studio for supported channels once the new reports are validated. Work with IT to enforce access controls.
- Forecasting models: Improve sales, ad budget and inventory forecasts. Document the assumptions, backtest against actuals and report error margins honestly.

Enablement and partnership

- Cross-functional partnership: Work with the Account and Creative teams to solve analytical problems and automate manual work. Turn recurring requests into standing Qore tools, and build compliant AI workflows for creative assets.
- IT collaboration: Agree a clear split with IT, written down: you own the use cases, and IT has final say on security, permissions and platform administration. Cross-train on urgent access tasks.
- Client intelligence layer (Month 7+): Build a governed, isolated AI context environment for each client. It should answer with citations and send actions only to approved Qore automations.

What Success Looks Like (First 90 Days)

- Qore migration underway, with role-specific SOPs published
- An AI usage guide (which tool for which task) live, and the first training wave delivered
- Trellis data reconciled against source consoles, with gaps documented
- A tool register in place and a monthly AI cost baseline established

What You Bring Must-haves

- 4-6+ years in analytics, BI or AI enablement roles




- Advanced Claude user and builder: Hands-on experience building shared workflows that teams rely on, using Skills, Projects, Connectors, MCP and Cowork or Claude Code
- Change management: You’ve rolled out tools, trained colleagues and measured adoption, rather than just announcing launches.
- Careful vetting: You read code before running it, test tools against known baselines and reject unsafe solutions.
- SQL and Python: Comfortable writing SQL for analysis, and able to use Python for API extraction, data cleaning and validation
- BI and reconciliation: You build reliable reports and routinely check totals and discrepancies against source systems.
- AI cost awareness: Current knowledge of the LLM landscape and token economics, and of how to match model size and cost to each task
- Clear documentation: You write short, accessible SOPs that busy, non-technical colleagues can follow.
- Good partner with boundaries: Helpful to internal teams, but able to say no to requests that don’t fit.
- Confidentiality: Disciplined about keeping data separate and protected across competing client brands
- Excellent written and spoken English, and comfortable working async across time zones

Nice-to-haves

- Advanced SQL (CTEs, window functions)
- Experience with BigQuery and Looker Studio
- Exposure to Amazon or marketplace data (Seller Central, Amazon Ads, retail analytics tools)
- Experience in an agency or multi-client environment

Benefits

- Competitive salary
- Prepaid medicine (medicina prepagada)
- Life insurance
- Birthday day off
- Indefinite-term labor contract with all statutory benefits

📌 Applied AI & Analytics Manager (Colombia)
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