Marcos Díaz Martín

Data & Analytics professional with 15+ years of experience in Business Intelligence, Data Management and Data Analytics. Specialized in transforming complex data into actionable insights, automating analytical processes, and supporting data-driven decision-making across multidisciplinary squads. Strong background in SQL, SAS, ETL, data governance and data modelling. Recognized for my ability to mentor colleagues, lead technical initiatives and deliver analytical solutions.

ING España & Portugal, Madrid

Data Analyst

APRIL 2022 – PRESENT

 Lead analytical support for 3 squads within the Everyday Engagement Tribe (MoneyUp services)

providing end-to-end data extraction, KPI tracking, and performance insights used in product decisions and customer communications via MU Cards.

 Designed and automated multiple SAS workflows for key Marketplace and Digital Engagement

Metrics (CEM), reducing manual processing time and increasing reliability of monthly reporting.

 Performed continuous monitoring and analyses to identify anomalous behaviors and potential account aggregators, reporting suspicious new Ips to Data Management for tagging in the DWH.

 Investigated the rise in PIN-related incidents by analyzing contacts, failed attempts, and error patterns to rule out attacks, identify root causes, and support mitigation measures.

 Conducted ad-hoc analyses and customer impact assessments for biometric mobile service,

supporting communication effectiveness and adoption tracking.

 Drove analytical requirements and data validation for the creation of the new Customer Device

Authentication Data Product, contributing to its structure, logic, and data specifications.

 Provide extraction, validation, and reporting support for high-visibility bank initiatives such as

Finalta, AEB, ABE and MIS/QPC, ensuring timely delivery and consistency across benchmarking submissions.

 Act as liaison between the DA Chapter and the Data Strategy area, consolidating concerns,

clarifying requirements, and ensuring governance alignment for modeling, definitions and quality topics.

 Serve as the reference point within the DA Chapter for all work related to the DWH Sunset initiative, leading the collection of legacy SQL queries and reporting progress in recurrent sessions.

 Lead the “Efecto Method” learning program for the DA Chapter, designing technical sessions and contributing to the upskilling of analysts in SQL, SAS, tools configuration and best practices.

Utad (Universidad Camilo José Cela), Madrid - Postgraduate course “Experto Big Data”

2016 - 2017

Final Project: Real-time processing using Apache Storm and OpenCV to detect faces and user comments in real time.

Universidad Politécnica, Madrid - Computer Science Engineering

2005 – 2011

Final Project: Data-Stream Management System integration in sensor networks. Real-time data processing.