Daniel Dantas
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Daniel Dantas Email & Phone Number

Analytics Manager at Mercado Pago Brasil at Mercado Pago Brasil
Location: São Paulo, Brazil 7 work roles 2 schools
1 work email found @ufl.edu LinkedIn matched
✓ Verified July 2026 4 data sources Profile completeness 100%

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Work email d****@ufl.edu
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Current company
Role
Analytics Manager at Mercado Pago Brasil
Location
São Paulo, Brazil
Company size

Who is Daniel Dantas? Overview

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Quick answer

Daniel Dantas is listed as Analytics Manager at Mercado Pago Brasil at Mercado Pago Brasil, a with 10700 employees, based in São Paulo, Brazil. AeroLeads shows a work email signal at ufl.edu and a matched LinkedIn profile for Daniel Dantas.

Daniel Dantas previously worked as Analytics Manager at Mercado Pago Brasil and Lead Data Scientist at Mercado Pago Brasil. Daniel Dantas holds Master Of Science - Ms, Agricultural Engineering from University Of Florida.

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Email format at Mercado Pago Brasil

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{first_initial}{last}@ufl.edu
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Profile bio

About Daniel Dantas

https://ddantasds.github.ioData Scientist with experience in different fields such as insurance, marketing, agriculture, and e-commerce. Motivated mainly by using data to better understand different process. Currently helping Mercado Pago to improve its business throughout data analysis.

Listed skills include Analysis, Analytics, Sas, Time Series Analysis, and 8 others.

Current workplace

Daniel Dantas's current company

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Mercado Pago Brasil
Mercado Pago Brasil
Analytics Manager at Mercado Pago Brasil
buenos aires, argentina
Employees
10700
AeroLeads page
7 roles

Daniel Dantas work experience

A career timeline built from the work history available for this profile.

Data Scientist

- Applied statistical techniques on GIS data to evaluate the impact of meteorological variables on crop yield (e.g., explain yield variability using drought index).- Created models using Machine Learning techniques (e.g., logistic regression, support vector machine, random forest, KNN) to locally improve leaf wetness classification (i.e., increased accuracy and true positive rate).

Mar 2015 - Sep 2018

Data Scientist

São Paulo Area, Brazil

Working with data analysis to bring solutions related to the auto insurance business:- Developed and updated statistical models to estimate auto risk premium (e.g., frequency and severity of car accident) using GLM techniques (Poisson and Gama distribution). - Developed and updated churn models for to estimate the probability of a client renew its insurance policy. Optimize the model to increase profitability (e.g., increase profitability constrained to a maximum of 20% of churn).-… Show more Working with data analysis to bring solutions related to the auto insurance business:- Developed and updated statistical models to estimate auto risk premium (e.g., frequency and severity of car accident) using GLM techniques (Poisson and Gama distribution). - Developed and updated churn models for to estimate the probability of a client renew its insurance policy. Optimize the model to increase profitability (e.g., increase profitability constrained to a maximum of 20% of churn).- Time series analysis to identify trends on auto insurance risk in order to adjust risk premium. - GIS analysis: Improved spatial information for auto insurance business reducing error by region.- Provide assistant to priority projects for the company – which included suggesting any new approach or analysis that could add value to the company. Show less

Jul 2012 - Mar 2015

Intern Of Business Intelligence Department

São Paulo E Região, Brasil

- Created and updated sales dashboard (KPIs) to manage the performance of sales team with different views. - Developed client segmentation as part of CRM for marketing strategies (Cluster analysis – Unsupervised learning: K-Means and Hierarchical). - Modeled churn using classification techniques (e.g., logistic regression). Implemented strategies to reduce churn via call center (discount decision tree). Responsible for updating and sending daily churn report.

May 2010 - Jun 2012

Intern Of Business Intelligence Department

São Paulo Area, Brazil

- Manipulated large datasets (millions of credit card transactions) using SQL to manipulate data (e.g., aggregating, merging) in order to create datasets for analysis. - Time series analysis to forecasts clients’ revenue to identify trends for marketing strategies. - Modeling transactions: Part of the team responsible for model transaction fraud risk (logistic regression).

Sep 2008 - Feb 2010
Team & coworkers

Colleagues at Mercado Pago Brasil

Other employees you can reach at mercadolibre.com. View company contacts for 10700 employees →

2 education records

Daniel Dantas education

FAQ

Frequently asked questions about Daniel Dantas

Quick answers generated from the profile data available on this page.

What company does Daniel Dantas work for?

Daniel Dantas works for Mercado Pago Brasil.

What is Daniel Dantas's role at Mercado Pago Brasil?

Daniel Dantas is listed as Analytics Manager at Mercado Pago Brasil at Mercado Pago Brasil.

What is Daniel Dantas's email address?

AeroLeads has found 1 work email signal at @ufl.edu for Daniel Dantas at Mercado Pago Brasil.

Where is Daniel Dantas based?

Daniel Dantas is based in São Paulo, Brazil while working with Mercado Pago Brasil.

What companies has Daniel Dantas worked for?

Daniel Dantas has worked for Mercado Pago Brasil, University Of Florida, Porto Seguro, Whirlpool Latin America, and Rede.

Who are Daniel Dantas's colleagues at Mercado Pago Brasil?

Daniel Dantas's colleagues at Mercado Pago Brasil include Camila Funes, Matias Vermehren, Matías Amden, Sergio Quijano, and Ricardo Rojas.

How can I contact Daniel Dantas?

You can use AeroLeads to view verified contact signals for Daniel Dantas at Mercado Pago Brasil, including work email, phone, and LinkedIn data when available.

What schools did Daniel Dantas attend?

Daniel Dantas holds Master Of Science - Ms, Agricultural Engineering from University Of Florida.

What skills is Daniel Dantas known for?

Daniel Dantas is listed with skills including Analysis, Analytics, Sas, Time Series Analysis, Regression Analysis, Cluster Analysis, Optimization, and Business Analysis.

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