🗂 Selected work

Real projects.
Real results.

Three engagements across insurance, international organisations, and a startup — each with a different challenge, the same north star: making data work harder for the people using it.

Case study 01
SDG Group
Manager, Data & AI Transformation · 2025–Present · Spain, Portugal, Colombia, Brazil
Insurance GenAI Multi-country Agentic AI
The challenge

Leading large-scale data and AI transformation programs for the insurance sector across four countries simultaneously — each with different regulatory environments, data maturity levels, and stakeholder dynamics.

The question was not just technical: how do you maintain quality and consistency across geographies while delivering at the pace a consulting engagement demands?

What we did
  • Led data platform modernisation coordinating engineering, analytics, and business teams across Spain, Portugal, Colombia, and Brazil
  • Systematically integrated GenAI tools across all project workflows — presentations, documentation, status reporting, meeting preparation
  • Contributed to MLOps practices and operationalisation of ML solutions for insurance use cases
  • Advised C-level and senior stakeholders on data transformation strategy and AI readiness
  • Designed capability building programs to strengthen data and AI competencies across client organisations
  • Managed agentic AI deployments automating project workflows and deliverable generation
Key insight
The biggest lever in a multi-country program is not technical — it's consistency of output. GenAI integration didn't just save time; it raised the quality floor for every deliverable across every country simultaneously.
~40%
Reduction in individual task time through systematic GenAI
4
Countries coordinated within a single program
C-level
Advisory across insurance sector clients
Live
Agentic AI frameworks deployed in production
⚡ Freed capacity redirected to higher-value advisory work
Case study 02
United Nations
Data Consultant · Geneva, Switzerland · 2022–2025
International org Databricks Power BI Data governance
The challenge

Supporting data management and analytics within a complex international organisation with strict information governance requirements, multiple stakeholder groups, and data assets spread across legacy systems.

The goal: improve the reliability, accessibility, and strategic use of data — within the governance constraints that are non-negotiable in an international institutional context.

What we did
  • Designed and implemented data quality and exception management processes, improving traceability of key data assets
  • Built Power BI environments enabling teams across departments to access operational insights in real time
  • Supported the migration of the data warehouse to Databricks — a major platform modernisation
  • Delivered training and adoption sessions, strengthening data literacy and self-service analytics across teams
  • Maintained governance standards appropriate to a sensitive multi-stakeholder international environment
Key insight
In a complex institutional environment, trust is the currency. Every data quality improvement and every dashboard that replaced a manual process built the credibility that made the larger platform migration possible.
Databricks
Major data warehouse migration delivered
Multi-dept
Power BI environments serving teams simultaneously
Geneva
International environment with strict governance
3 yrs
Sustained engagement across data quality, BI, and platform
🌍 Manual reporting replaced with real-time self-service analytics
Case study 03
datalitiks
Founder & CEO · Malta · 2022–2024
Startup ESG data GenAI Product strategy
The challenge

Building an ESG data and analytics platform from scratch — with a lean team, limited resources, and a market that in 2022 was only beginning to understand why it needed structured ESG data.

The challenge was simultaneously a product problem, a data architecture problem, and a market education problem.

What we did
  • Defined the data strategy and product vision — transforming fragmented ESG data into structured, actionable insights
  • Designed the analytics framework and data architecture supporting ESG measurement across multiple client sectors
  • Integrated ChatGPT from week one into core development and content workflows — one of the earliest systematic GenAI adoptions in the ESG space
  • Built and led a multidisciplinary team of data scientists, engineers, and ESG specialists
  • Championed the "Data for Good" concept — aligning data practices with sustainability goals
  • Supported clients with GRI and UN SDG reporting frameworks across multiple sectors
Key insight
Early GenAI adoption was not a side project — it was a core strategic decision that determined whether we could survive as a lean team. Integrating AI into every workflow from day one compressed timelines and created a culture of continuous AI experimentation.
~30%
Faster platform development through GenAI integration
~40%
Lower content production costs vs traditional approach
2022
Early adopter before GenAI became mainstream
Multi
Frameworks: GRI, UN SDGs, sector-specific standards
🚀 Lean team output equivalent to a significantly larger headcount

Want to work on
something like this?

I'm always open to conversations about data transformation, AI strategy, and what it takes to make these programs actually work.

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