Francisco Yirá

Francisco Yirá

Data Scientist

Toronto, Canada

Hi! I’m Francisco, a data scientist with 6 years of experience across different industries (including retail, Fintech and telco), currently studying Applied AI Solutions Development at George Brown College in Toronto. I am an expert in SQL, R, and Python, and certified on AWS and Tableau.

I love using statistical modelling and data to help businesses quantify the impact of what they do and make data-driven decisions. I also enjoy improving business outcomes through machine learning, automation and data management best practices.

Resume in PDF

Interests
  • Machine Learning and AI
  • Causal Inference and Experimentation
  • Data Visualization, Dashboards and Reports
  • Automation
  • MLOps and Data Engineering
Degrees
  • Applied A.I. Solutions Development Postgraduate Diploma, 2024

    George Brown College

  • Diploma in Econometrics, 2020-2021

    University of Chile

  • Diploma in Big Data, 2017-2018

    Pontifical Catholic University of Chile

  • BSc in Economics, 2010-2015

    University of Chile

Skills

R
Python
Advanced SQL
Visualization and Dashboards
Causal Inference and Experimentation
Machine Learning
Effective Communication with Stakeholders
Amazon Web Services
Git and Command Line

Portfolio

Personal projects, blog posts, publications and talks

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Exercises of the book 'R for Data Science'
Exercises of the book 'R for Data Science'

My solutions to exercises of R for Data Science, a book about how to use the tidyverse ecosystem in R to perform end-to-end data analyses, written by the creators of dplyr and ggplot2 themselves.

Work Experience

 
 
 
 
 
MACH (Fintech)
Data Scientist
Aug 2022 – Jan 2024 Santiago, Chile
  • Enabled targeting of high-potential app users by integrating PySpark machine learning models with CRM data through SQL pipelines on Apache Airflow.
  • Increased marketing spend efficiency by conceiving high-ROI initiatives through ideation and A/B testing process, leveraging Amplitude reports and agile methodologies.
  • Proposed and implemented an experimentation framework for A/B testing best practices.
  • Trained predictive machine learning models using AWS cloud infrastructure (SageMaker, Athena and Glue) and PySpark.
  • Assessed ROI of referral campaigns via advanced causal inference techniques when A/B Testing was not feasible.
  • Developed user-friendly dashboards on AWS QuickSight to enable C-level executives to conduct simulations and what-if analysis for promotional campaigns on our app home screen.
 
 
 
 
 
WOM (Telecommunications)
Data Scientist
Jan 2020 – Oct 2021 Santiago, Chile
  • Guided deployment of new network infrastructure, identifying areas where upgrades would reduce churn the most.
  • Tracked network deployment results via geospatial dashboards blending network KQIs with churn and NPS metrics.
  • Boosted conversion of telesales by developing purchase propensity predictive models with LightGBM.
 
 
 
 
 
Walmart Chile (Retail)
Data Scientist
Oct 2018 – Jan 2020 Santiago, Chile
  • Developed data transformation processes and implemented machine learning models that allowed the deployment of a personalized marketing strategy for the company’s most important local brand. This included the development of churn models and clustering on transactional data.
  • Led the development of an internal R package aimed at streamlining processes and accelerating deliveries in our area (find out more here).
  • Led the impact evaluation of the personalised marketing project by designing, implementing, and supervising A/B tests, in close collaboration with the CRM Ops team. This included devising solutions for increasing statistical power in contexts of small treatment effects.
  • Introduced the use of version control and unit tests to the team.
 
 
 
 
 
Walmart Chile (Retail)
Data Analyst
Nov 2017 – Oct 2018 Santiago, Chile
  • Provided data-driven insights to marketing and merchants, leveraging econometrics and clear storytelling.
  • Automated complex, ad-hoc reports through R Markdown and Tableau, increasing throughput of our team.
  • Assessed the impact of key, C-level decisions via causal inference techniques such as Difference in Differences.

Formal Education

Degrees

 
 
 
 
 
George Brown College, School of Computer Technology
Postgraduate Diploma in Applied A.I. Solutions Development
Jan 2024 – Present Toronto, Canada

A one-year post-graduate program blending computer science, mathematics, and business to develop AI solutions.

Cumulative GPA: 3.94.

Academic Award:

Coursework Highlights:

  • Machine Learning I and II: usage of sci-kit learn, openCV (computer vision), NLP and audio-processing libraries.
  • Data Visualization Techniques: advanced use of Tableau for reporting and data storytelling.
  • Big Data Techniques: Azure Fundamentals, Hadoop ecosystem (HDFS, Pig, Hive, Beeline), Spark, and ETL processes with SQL Server Integration Services.
  • Foundations of Data Management: Data Management Body of Knowledge framework.
  • Applied Mathematical Concepts for Machine Learning: linear algebra, matrix factorization, TF-IDF, gradient descent, convolution, Fourier transforms, signal processing.
  • Design Thinking for AI.

Relevant Documents (access available upon request):

 
 
 
 
 
University of Chile, Faculty of Economics and Business
Diploma in Applied Econometrics
Aug 2020 – May 2021 Santiago, Chile

10-month program covering experimental design, causal inference with observational data and time series analysis.

Relevant Documents (access available upon request):

 
 
 
 
 
Pontifical Catholic University of Chile, Faculty of Engineering
Diploma in Big Data
Aug 2017 – May 2018 Santiago, Chile

144-hour program covering the fundamentals of machine learning, recommender systems, Hadoop, parallel computing and graph theory.

Relevant Documents (access available upon request):

 
 
 
 
 
University of Chile, Faculty of Economics and Business
BSc in Economics
Mar 2010 – Dec 2015 Santiago, Chile

Graduated with distinction. 5-year program.

Relevant Documents (access available upon request):

Additional Education and Certifications

Validation of core Tableau knowledge and hands-on development skills with Tableau Desktop, Tableau Prep, and Tableau Server, including connecting to data sources, preparing data for analysis, creating impactful visualizations with complex data, and effectively communicating insights through interactive dashboards and storyboards.
See certificate
Achieved badge from IBM demonstrating foundational skills in applying design thinking principles at scale, focusing on user-centric research, innovative problem-solving, and compelling storytelling to address and understand user challenges.
See certificate
DataCamp
Big Data with PySpark
Completed 24-hour course track on Apache Spark using the PySpark Python API. The track included courses on PySpark basics, data cleaning, feature engineering, machine learning, and building recommendation engines.
See certificate
Earned an industry-recognized credential that validates foundational understanding of AWS Cloud concepts, services, and terminology. Demonstrated knowledge of cloud economics, security, architecture, and support models.
See certificate
Coursera
DevOps on AWS
30-hour specialisation on DevOps concepts and practices in the AWS Cloud. Learned how to use AWS services and tools for Continuous Integration and Delivery, serverless deployment, and monitoring and logging.
See certificate
4-hour course on hierarchical and mixed effects models in R with the lmer package. Learned how to fit and compare random effects models for nested and longitudinal data.
See certificate

Contact Me

Let’s connect! I actively monitor this form and welcome new project opportunities.