Jose Rico

Pricing Analyst | MSc Data Analytics

About Me

Jose Biking

Hello! I’m Jose, a Spaniard who has been living in Ireland for six years. Currently, I work as a Pricing Analyst at Cardinal Health, supporting commercial teams with data migration and visualization, ensuring accurate data flow between Salesforce and SAP.

I recently graduated with a Master of Science in Data Analytics from CCT College, Dublin, where I developed skills in Machine Learning, Data Preparation & Visualisation, and Big Data Processing. My final project focused on building a Federated Learning (FL) server to simulate real-world decentralized model training, enhancing model accuracy for various scenarios.

This experience gave me hands-on expertise in advanced data systems, and I’m passionate about leveraging data to drive impactful business solutions. I’m excited to take on new challenges as I continue my journey in data analytics.

Experience

Senior Pricing Analyst at Cardinal Health

Apr. 2020 - Present

Creating and automating reports through SQL and Python based on stakeholders' requirements. Building dashboards in Power BI to drive insights regarding KPIs. Maintaining offers and tenders prices in SAP, ensuring accurate uploads to avoid future price discrepancies. Investigating customer price discrepancies and implementing preventive measures to enhance the company's financial health. Collaborating with the analytics team to design, develop, and deploy powerful business metrics and reporting.

Community Operations Analyst at Facebook by CPL

Jan. 2019 - Mar. 2020

Identifying and escalating cases regarding safety according to Facebook policies. Enforcing and improving Facebook policies by working closely with the global policy team. Monitoring trends and rating performance across Spanish communities, researching and troubleshooting variations in performance.

Claims Manager at Puertas Castalla, S.L.

Mar. 2017 - Oct. 2018

Managing fraud prevention related to inappropriate brand use. Analyzing performance data to enhance productivity and quality ratios, considering customer feedback. Developing and implementing quality product standards to meet ISO 9001:2015 quality standards and ISO 14001:2015 environmental requirements.

Account Manager at Puertas Castalla, S.L.

Oct. 2014 - Nov. 2016

Managed orders, stock, and inventory while maintaining strong customer relationships. Oversaw a portfolio of nearly 200 client accounts, acting as the primary liaison between the consumer and the corporation.

Education

Master of Science in Data Analytics

CCT College, Sept. 2023 - Oct. 2024

Grade: 6.2 (Second-Class Honours)

Level 9 National Framework of Qualification (NFQ)

Higher Diploma in Science in Computing - Software Development

Dublin Business School, Sept. 2020 - Sept. 2022

Grade: 7.3 (First-Class Honours)

Level 8 National Framework of Qualification (NFQ)

Diploma in Big Data for Business

Dublin Business School, Sept. 2019 - May 2020

Level 7 National Framework of Qualification (NFQ)

Bachelor’s Degree in Business & Management

University of Alicante, Sept. 2010 - Jun. 2016

Level 6 European Qualification Framework (EQF)

Skills

Programming Languages

Python, R, C#, JavaScript

Other Languages

SQL, HTML, CSS, LaTeX

Tools

Tableau, Power BI, Linux

ERP's

SAP & Salesforce

ML

K-Means, GridSearch, NN's, CNN's

Big Data

Hadoop, Spark, MapReduce, Hive, Cassandra, MongoDB

MSc Assignments

Semester One CA1

Recent Demographic History in the Republic of Ireland.

Semester One CA2

Analysis of the Irish Transport Sector: A Comparative Study with EU Countries.

Semester Two CA1

Storage Solutions and Data Analytics: RDBMS, Hadoop and APIs in Neural Networks Contexts.

Semester Two CA2

Big Data Storage, Processing, and Advanced Data Analytics for Twitter Data.

MSc Capstone Project

Federated Learning: Evaluating Popular Frameworks and Developing a Cross-Client Horizontal Server

This project investigates Federated Learning (FL), a decentralized machine learning approach that enhances data privacy. It evaluates five popular FL frameworks and develops a cross-client horizontal FL server for both technological and medical scenarios using IID and non-IID data. The findings reveal improved model accuracy in the technological scenario but a slight decline in the medical scenario. The research highlights the potential of FL while identifying limitations and areas for future improvement in server infrastructure and privacy concerns.