Carlos G.

I built a number of systems, integrated in customer product development teams. Most notably:

At Staq.io, a Fintech startup (GCP, RunPod):

• AI prototype to assist compliance officers. End-to-end NLP pipeline from PDF data
  extraction and transformation, through model fine-tuning, to RaG and prototype UI.

At Intel471, a Cybersecurity company (AWS):

• Multilingual NLP pipeline for knowledge extraction from discussion forums. Data curation, extraction, transformation and annotation. Model fine tuning, custom decoding, evaluation and deployment. Data visualisation.

At Bank Al Etihad, a Retail Bank (AWS + On-Premise):

• Analytics pipeline and data warehouse. Anonymisation. Streaming data fusion.
• Bespoke offering recommender from transaction data.
• Deposit rate optimisation, causal estimation. Churn, loan, and card risk models.

At Verto Analytics, a Behavioural Analytics startup (AWS):

• Processing pipeline optimisation
• Workflow orchestration for deliveries.

At MarkaVIP, an E-commerce startup emphasizing Flash Sales (AWS):

• Bespoke low latency recommender

My focus was on laying the foundation for Data Science, to enable sustainable results.

Data Engineering achievements:

• Built and deployed a foundational analytical pipeline. (AWS, Kinesis, Redshift, Spark)
• Integrated continuous data ingestion from key systems into the pipeline, whenever
  practical through low latency interfaces such as MySQL database replication.
• Migrated interaction tracking and key analytical systems to the pipeline.

Notable Data Science work:

• Modelled interventions on customer experience to address returns and cancellations.
  Built a policy optimiser, through retrospective simulation with historical data. (Python,
  Kinesis, Redshift)
• Improved profitability by optimising basket constraints and incentives. (Python/PuLP)
• Performed retrospective sourcing performance and pricing analysis. (Python)