Alvaro Leonardo Garcia Arroyo
Applied Data Scientist | Brand measurement in generative AI engines
I build measurement systems that say when a movement in the data means something, and when it is just noise
Hi, my name is
About me
Applied Data Scientist. Six years building measurement systems on marketing, financial and public health data: deciding what to measure, with which method, and when a movement means something rather than being noise. Today, at LLYC, I am responsible for brand visibility measurement in generative AI engines (ChatGPT, Perplexity, Copilot, Google AI Overview) for more than 13 brands across six markets in Latin America and North America. I design the audit method, the prompt sets, and the criteria that decide whether a movement is attributable to the brand or is the engine moving on its own. My background is applied time series econometrics, which I also teach at UPC: ARMA, GARCH, VAR, VECM and machine learning for time series. I also collaborate on the agentic workflows the team uses to deliver to clients, and I do research at the RIEF.
Here are a few technologies I've been working with recently:
- Python
- Tensorflow
- R
- Git/Github/Control-Version
- DAX
- SQL
- Power BI
- Brandwatch
- Power Query
- Power Pivot
- Excel
- Econometrics
Experience
Technologies used: Python, R, Power BI, Power Query, DAX. Responsible for brand visibility measurement in generative AI engines (AEO/GEO) for more than 13 brands across six markets in Latin America and North America: Alicorp, Gentera, Compartamos Banco Mexico, Concredito Mexico, Yastas Mexico, Aterna Mexico, Banco Popular Dominicano, Honda Mexico, Acura Mexico, Inter-American Development Bank, Bimbo Mexico, Bimbo Canada and Grupo Roggio Argentina. I design the audit method and the prompt sets, define the criteria that separate a real movement from engine noise, and specify the technical recommendations the client receives: AI crawler access (robots.txt, llms.txt), schema.org structured data, indexable FAQs and owned-content strategy. I also coordinate teams of 2 to 3 analysts on roughly a third of the projects.
Technologies used: Brandwatch, Power BI, Power Query, DAX, R, Gephi, Netai, SCRUM. Social listening at scale: reports, studies and dashboards on the evolution of conversation volume across social networks, press and blogs, for brand reputation monitoring, trend detection and crisis prevention. Design of new monitoring KPIs and network analysis with graph theory. Brands worked with include Coca-Cola, 3M, Hunt Oil, Galderma, Banco Atlantida, Gobierno de Mexico and Grupo El Comercio.
Technologies used: Python, Tensorflow.
Temporary contract awarded after winning a scholarship from Google India and Turkey to participate in training in advanced and current Deep Learning architectures. The following architectures were reviewed in mathematical and applied detail : Neural Networks, Convolutional Neural Networks, RecurrentNeural Networks, Long Short Term Memory (LSTM), Bidirectional LSTM, Transformers, among others
Temporary contract awarded after winning a scholarship from Google India and Turkey to participate in training in advanced and current Deep Learning architectures. The following architectures were reviewed in mathematical and applied detail : Neural Networks, Convolutional Neural Networks, RecurrentNeural Networks, Long Short Term Memory (LSTM), Bidirectional LSTM, Transformers, among others
Technologies used: Power BI, Power Query, DAX, SCRUM, Miro and Bizagi are used
Business Intelligence that provides support to "Minera Las Bambas". As part of my main activities, I have developed dashboards for the efficiency, volume and asset management superintendencies within the entity. Likewise, I have led report automation projects, migrating from traditional PDF's or Power Point's to more interactive reports.
Business Intelligence that provides support to "Minera Las Bambas". As part of my main activities, I have developed dashboards for the efficiency, volume and asset management superintendencies within the entity. Likewise, I have led report automation projects, migrating from traditional PDF's or Power Point's to more interactive reports.
Technologies used: Excel and Stata were used
I provide support to Professor Juan Tenorio (PhDc in Economics at U. Michigan) teaching the practical classes of the Econometrics II course, you can view the recordings and material used here. Simple Linear Regression, Regression with Instrumental Variables, Logit and Probit Regression, and Regression with Fixed and Random Effects were the reviewed topics.
I provide support to Professor Juan Tenorio (PhDc in Economics at U. Michigan) teaching the practical classes of the Econometrics II course, you can view the recordings and material used here. Simple Linear Regression, Regression with Instrumental Variables, Logit and Probit Regression, and Regression with Fixed and Random Effects were the reviewed topics.
Technologies used: R, Python, Excel, Power Query, DAX and Power BI are used
I bring support to professor Renato Lazo (PhDc in Finance at Ottawa University) in the Asset Pricing Research Initiative at RIEF. As part of my main activities I create a new Dataset about Mutual Funds in Peru and I develope a Interactive Dashboard with it. Also I participate as Co-Author in new Paper about the channels of prediction of Mutual Fund Flow's for Peru
I bring support to professor Renato Lazo (PhDc in Finance at Ottawa University) in the Asset Pricing Research Initiative at RIEF. As part of my main activities I create a new Dataset about Mutual Funds in Peru and I develope a Interactive Dashboard with it. Also I participate as Co-Author in new Paper about the channels of prediction of Mutual Fund Flow's for Peru
Intern, Deputy Superintendency of Risks
-
Superintendency of Stock Market
September 2021 - January 2022
Technologies used: R, Power BI, Power Query and DAX were used
I elaborated and automated the publication of Dashboards related to the monitoring of COVID-19 at the international level, local and international Macro-financial Variables and Risk Matrices. I supported in the calculation of liquidity risks for Mutual Funds.
I elaborated and automated the publication of Dashboards related to the monitoring of COVID-19 at the international level, local and international Macro-financial Variables and Risk Matrices. I supported in the calculation of liquidity risks for Mutual Funds.
Technologies used: Power Point, Power BI, Power Query and Excel were used
I provided support in the preparation of sectoral reports, as well as the development and automation in the publication of monitoring reports on macroeconomic and financial variables.
I provided support in the preparation of sectoral reports, as well as the development and automation in the publication of monitoring reports on macroeconomic and financial variables.
Technologies used: R, Python, Excel, Power BI, Power Query, DAX and Power Point were used
I supported the development and automation of Dashboards of great impact on health and business management issues. I participated in the elaboration of the Essalud heat map that was awarded for good practices in social security at a national and international level.
I supported the development and automation of Dashboards of great impact on health and business management issues. I participated in the elaboration of the Essalud heat map that was awarded for good practices in social security at a national and international level.
Education
2016-2021
Bachelors in Economics
Peruvian University of Applied Sciences
Economics and International Business, Upper fifth, Graduated in third place.
Projects
Power BI
DAX
Power Query
Mutual Fund Analysis Project
A highly innovative analysis with the creation of new database about Mutual Funds in Peru.
Python
R
Power BI
DAX
Bloomberg
MacroFinancial Analysis Project for SMV
A innovative way to centralize important information about international and national markets, covid-19 and Economics indicators provided by BCRP, INEI, etc.
Python
R
Power BI
DAX
Bloomberg
International Covid-19 Analysis Project for SMV
A innovative way to Visualize data about Covid-19 with information provided by OurWorld in Data.
Lectures Websites 🧠
Eviews
Python
Econometrics (VAR, ARMA, GARCH)
Statistics
Excel
Macroeconometrics Course
Course taught in the semester 2023-I for the students of the Peruvian University of Applied Sciences.
Python
Tensorflow
Deep Learning
Deep Learning Course
Course taught for the Summer School in Economics and Finance 2023
Stata
Econometrics
Statistics
Excel
Ecomometric II Course
Course taught in the semester 2022-I for the students of the National University of Engineering.
Achievements
Get in Touch
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