Bruno Piato Email & Phone Number

Jundiaí, Sp, Br

I contributed to the development and optimization of data acquisition pipelines, utilizing a variety of technologies such as Python, PostgreSQL, and BigQuery. I gained hands-on experience working with cloud infrastructures, including Microsoft Azure and Google Cloud Platform virtual machines, to handle large-scale data processing and storage. My role involved automating data workflows, optimizing database queries, and ensuring the efficient transfer of data across cloud platforms to support critical business decisions. This experience deepened my understanding of cloud architecture and scalable data solutions.

Jundiaí, São Paulo, Brasil

Acting in the business rules comprehension and their translation into operations research model for inventory allocation optimization using Python and SQL.

Jundiaí, São Paulo, Brasil

Utilized ETL concepts, development and modeling of dimensional and relational databases to build the data pipeline to be used in the LRP (Long-Range Planning) solution for the supply chain area of Coca-Cola Latin America. Created a data warehouse in PostgreSQL stored on the Microsoft Azure cloud service. Actively implemented and optimized SQL queries to the database and developed the database architecture. Worked alongside the customer to develop dashboards and reports in Power BI to track business metrics and KPIs. Additionally, participated in the development of an Excel add-in to ingest data and send it to the database using a Python script for connection and data validation.This project resulted in the automation of the ETL process and increased data governance by stakeholders, as data began to be ingested via an Excel add-in, conducted through pipeline that processes the data, stored in a cloud service data warehouse, and consumed in a Power BI report automatically.Tools: SQL, PostgreSQL, Microsoft Azure, Microsoft Excel, Microsoft Office, Microsoft 365 and Microsoft PointShare

Jundiaí, São Paulo, Brasil

Digital content producer for the Comunidade DS YouTube channel and other media such as Medium blog, LinkedIn and Instagram posts, etc. The contents comprehend Python, R, SQL, software engineering, Git, GitHub, Streamlit, machine learning, artificial intelligence, data carreers and other data science related subjects.

Jundiaí, São Paulo, Brasil

For ten years I worked as a mid and high school teacher, which provided me the chance to develop my communication and managing skills.

Jundiaí, São Paulo, Brasil

- Situation: The genus of frogs Brachycephalus comprises more than 35 species, and until recently, there was no hypothesis regarding the evolutionary relationship among its elements. Additionally, it exhibits a high rate of occurrences restricted to small locations or altitude ranges. Understanding the relationships and ecological niche occupation of these animals is essential for a better comprehension of their evolutionary history and conservation strategies.- Task: Collect publicly available genetic data from databases like GenBank to reconstruct their relationships and employ statistical and machine learning tools to reconstruct the ecological niche occupied and the ecological climatic requirements of each species.- Action: The entire work was completed exclusively using the R statistical environment. I acquired genetic data available for 29 out of the 35 species of the Brachycephalus genus and reconstructed the evolutionary history using Bayesian inference (MrBayes and BEAST). Utilizing machine learning algorithms implemented in the BIOCLIM package, I reconstructed the fundamental aspects of the climatic ecological niche of the species. This allowed for statistical comparisons and inferences regarding how much the ecological niches remain the same or change over time for the species, given the known relationship among them.- Results: I identified the evolutionary lineages of the genus and found a certain degree of maintenance of their niche, indicating that the evolution of niche occupation does not occur intensely and may not keep pace with the climatic changes these species will face.- Conclusions: Using a statistical and evolutionary approach to address conservation issues in the face of climate change is crucial. This enables us to consider the entire complexity of the phenomena of interest.- Tools: R language, Bayesian inference, BIOCLIM, BEAST2, MrBayes, ENMTools, MaxEnt, NicheAnalyst, PCA, raster, HDMD, adephylo, etc.

Santo André, São Paulo, Brasil

Abstract: I used genetic and biogeographic data to assess the evolutionary processes acting on populations of two invertebrate species with highly distinct geographical distributions.- Situation: As populations of a species become separated, genetic mutations that occur become restricted to each population, interrupting gene flow. This leads to the process of speciation, where two or more populations move towards originating new species.- Task: Use genetic and biogeographic data to estimate the degree of separation between populations of two species, employing statistical models and machine learning to reconstruct the likely geographical distributions of the species since the last Ice Age (around 22 thousand years ago).- Action: I used the R programming language to explore population genetics descriptive statistics to diagnose the degree of segregation between populations and to implement statistical models, reconstructing the likely past distributions of the species.- Results: I identified that, despite populations having a significant degree of genetic segregation due to isolation caused by the advance of glaciers during the last glaciation, the subsequent reestablishment of contact between them prevented the completion of the speciation process.- Conclusions: Biogeographic statistical modeling combined with population genetics statistics provides a robust framework for elucidating evolutionary processes that occurred in the past and continue to occur today.- Tools: R programming language, BIOCLIM, WORLDCLIM, Excel, MEGA X, MrBayes, Bayesian statistics, machine learning, AUC, ROC curve, PCA.

Rio Claro, São Paulo, Brazil

- Situation: Within the UNESP-Rio Claro campus, there is a large forested area. However, the fauna of seed-dispersing birds and the main tree species dispersed by birds were not thoroughly understood.- Task: Conduct systematic observations of bird-plant interactions to identify the main species of seed-dispersing birds and the primary tree species dispersed by birds, developing an analysis of the data in the form of a report to guide decision-making within the campus.- Action: Throughout the four seasons, I conducted systematic observations of interactions between birds and tree vegetation, identifying the species involved and quantifying the interactions. After data acquisition, I developed an analytical report synthesizing the information in the form of graphs and descriptive statistics.- Results: I was able to list the ten tree species most accessed by birds, as well as the ten key bird species for seed dispersal within the campus.- Conclusions: In tree planting and the creation of ecological corridors, priority should be given to the use of these species to maximize interactions with frugivorous birds and, consequently, the dispersal of these species along the relevant sections.- Tools: Microsoft Excel, Microsoft Word, and BioEstat

Tecnólogo Em Ciências De Dados, Information Technology

Mestrado, Evolutionary Biology, Finished With Concept A In Every Subject.

I studied the impact of Pleistocene climate changes on the genetic contitution and geographic distribution of several populations of two.

Bacharelado E Licenciatura, Biology/Biological Sciences, General

During my bachelor in Biological Sciences I studied animal behavior and ecology. At my first scientific iniciation I studied.