Dalton Zurita, Developer in Guayaquil, Guayas, Ecuador
Dalton is available for hire
Hire Dalton

Dalton Zurita

Verified Expert  in Engineering

Data Scientist and Developer

Location
Guayaquil, Guayas, Ecuador
Toptal Member Since
October 20, 2022

Dalton is a data scientist with five years of experience. He is proficient in data processing, predictive modeling, and data visualization to solve challenging business problems. Dalton has developed different machine learning models, such as churn prediction, sales forecasting, and topic identification. He is keen on acquiring new skills quickly and offering the best solutions.

Portfolio

StratPlus
SQL, Python, Azure, PySpark, Azure Databricks, Azure Synapse...
Claro Ecuador
Python, Machine Learning, Data Science, SQL, Deep Learning, Tableau...
IASA Caterpillar
SQL, Python, Microsoft Power BI, ETL, Data Analysis, Machine Learning...

Experience

Availability

Part-time

Preferred Environment

MacOS, Windows, Jupyter Notebook

The most amazing...

...thing I've developed is a customer churn prediction model to help the company retain its customers and prevent them from joining the competition.

Work Experience

Data Engineer

2023 - 2024
StratPlus
  • Wrote Spark code to process, clean, and transform data using Azure Databricks.
  • Optimized and managed Spark jobs to improve performance and reduce costs.
  • Utilized Power BI desktop to design interactive reports.
Technologies: SQL, Python, Azure, PySpark, Azure Databricks, Azure Synapse, Azure Data Factory, Azure Data Lake, Microsoft Power BI, Requirements Analysis, Consulting, Azure Service Fabric

Data Scientist

2019 - 2023
Claro Ecuador
  • Developed a customer churn prediction model to predict which customers are more likely to abandon the company and go to the competition. The model helped the company save money by retaining its customers with marketing actions.
  • Created a sales forecast model to predict the company's and the competition's future sales. I used techniques like SARIMAX and machine learning models.
  • Created ETLs to extract, transform, and load data to have the data cleaned in different databases. This information was ready to be used in dashboards and machine learning models.
  • Built dashboards to create insights for the company using business intelligence tools like Tableau. The dashboards were utilized to create important KPIs for data monitoring.
Technologies: Python, Machine Learning, Data Science, SQL, Deep Learning, Tableau, Microsoft Power BI, Predictive Modeling, Data Analytics, Regression Modeling, Statistics, Data Analysis, Dashboards, Business Intelligence (BI), Data Visualization, Jupyter, Linear Regression, Databricks, DAX, ETL, Jupyter Notebook, Analytics, Business Analysis, Python 3, Pandas, PostgreSQL, NumPy, Data Engineering, Data Pipelines, Reports, Microsoft Excel, Forecasting, Sales Forecasting, Azure Databricks, Predictive Analytics, Algorithms, R, Windows, MacOS, Big Data, GPT, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), Stored Procedure, SQL Stored Procedures, XML for Analysis (XMLA), SQL Server Integration Services (SSIS), API Integration, Cron, Dashboard Design, Web Analytics, BI Reports, TensorFlow, Neural Networks, Data Cleansing, Datasets, Snowflake, Apache Airflow, Amazon QuickSight, Data Build Tool (dbt), ETL Tools, Amazon Web Services (AWS), Data, GitHub, Fivetran, Microsoft SQL Server, Microsoft Azure, Azure, Time Series, Financial Modeling, Time Series Analysis, Amazon SageMaker, PyTorch, Diffusion Models, Variational Autoencoders, MLM, Data Reporting, MySQL, Finance, Azure Data Factory, Azure Synapse, Looker, Google Data Studio, BigQuery, Vertex, Google Cloud Platform (GCP), Artificial Intelligence (AI), Requirements Analysis, Consulting, Azure Service Fabric

Business Intelligence Analyst

2018 - 2019
IASA Caterpillar
  • Developed dashboards to create KPIs for different company departments using Power BI.
  • Created ETLs to extract, transform, and load data in order to have the data cleaned in different databases. This information was ready to be used in dashboards and machine learning models.
  • Built a sales forecast model to predict the company sales and trends in the market share.
Technologies: SQL, Python, Microsoft Power BI, ETL, Data Analysis, Machine Learning, Data Science, Predictive Modeling, Data Analytics, Regression Modeling, Dashboards, Business Intelligence (BI), Data Visualization, Jupyter, DAX, Tableau, Jupyter Notebook, Analytics, Business Analysis, Python 3, Pandas, PostgreSQL, NumPy, Data Engineering, Data Pipelines, Reports, Microsoft Excel, Databricks, Forecasting, Sales Forecasting, Azure Databricks, Predictive Analytics, Algorithms, R, Windows, MacOS, Big Data, Stored Procedure, SQL Stored Procedures, XML for Analysis (XMLA), SQL Server Integration Services (SSIS), API Integration, Cron, Dashboard Design, BI Reports, TensorFlow, Neural Networks, Data Cleansing, Datasets, Snowflake, Apache Airflow, Amazon QuickSight, Data Build Tool (dbt), ETL Tools, Amazon Web Services (AWS), Data, GitHub, Fivetran, Microsoft SQL Server, Time Series, Time Series Analysis, Data Reporting, MySQL, Azure Data Factory, Azure Synapse, Requirements Analysis

Business Intelligence Intern

2018 - 2018
Claro Ecuador
  • Built dashboards with business intelligence tools for the commercial team with insights into the sales database.
  • Developed ETLs to extract data from different data sources.
  • Created a customer clustering algorithm to identify customers based on their characteristics.
Technologies: Microsoft Power BI, Tableau, ETL, Python, DAX, Data Analysis, Business Intelligence (BI), Data Visualization, SQL, Data Analytics, Dashboards, Analytics, Business Analysis, Python 3, Pandas, PostgreSQL, NumPy, Data Engineering, Data Pipelines, Reports, Microsoft Excel, Windows, Stored Procedure, SQL Stored Procedures, XML for Analysis (XMLA), SQL Server Integration Services (SSIS), Cron, Dashboard Design, BI Reports, TensorFlow, Neural Networks, Data Cleansing, Datasets, Apache Airflow, ETL Tools, Data, Microsoft SQL Server, Data Reporting, MySQL

Business Intelligence Intern

2016 - 2017
Banco Amazonas
  • Built dashboards using Power BI with customer and sales data to present them to stakeholders.
  • Generated reports using SQL to query the databases.
  • Developed ETLs to have the data ready to use for the different dashboards.
Technologies: Microsoft Power BI, SQL, Dashboards, DAX, Data Analysis, Business Intelligence (BI), Data Visualization, Data Analytics, Analytics, Business Analysis, Python, Python 3, Pandas, PostgreSQL, NumPy, Reports, Microsoft Excel, Windows, Stored Procedure, SQL Stored Procedures, Cron, BI Reports, Data Cleansing, Datasets, ETL Tools, Data, Microsoft SQL Server, MySQL

Twitter Topic Classification

A machine learning model to classify tweets on different topics depending on their content. The project consisted of developing a complete process, from downloading tweets with an API to the model deployment.

Dashboard with Geospatial Data

Developed a dashboard using Power BI. It consisted of different KPIs of historical sales data. The data sources were tables from SQL Server and Shapefiles with geospatial data. It showed insights into different cities' sales on a map.

Customer Clustering Dashboard

This project combined knowledge of machine learning and business intelligence. In the first phase, I developed a customer clustering model in Python to discover groups of customers based on their characteristics and behavior. In the second phase, I created a dashboard using Power BI with the output of the model to present the insights to the managers.

Languages

Python, SQL, Python 3, Stored Procedure, Snowflake, R

Frameworks

Spark

Libraries/APIs

Pandas, NumPy, TensorFlow, PyTorch, PySpark

Tools

Tableau, Microsoft Power BI, Jupyter, Microsoft Excel, Cron, Apache Airflow, Amazon QuickSight, GitHub, Amazon SageMaker, Looker, BigQuery

Paradigms

Data Science, ETL, Business Intelligence (BI), Requirements Analysis

Platforms

Jupyter Notebook, MacOS, Windows, Databricks, Amazon Web Services (AWS), Azure, Azure Synapse, Google Cloud Platform (GCP), Azure Service Fabric

Storage

PostgreSQL, Data Pipelines, SQL Stored Procedures, SQL Server Integration Services (SSIS), Microsoft SQL Server, MySQL, Google Cloud

Other

Machine Learning, Deep Learning, Data Analysis, Big Data, Natural Language Processing (NLP), Predictive Modeling, Data Analytics, Regression Modeling, Statistics, Dashboards, Data Visualization, Linear Regression, DAX, Analytics, Business Analysis, Data Engineering, Reports, Forecasting, Sales Forecasting, Azure Databricks, Predictive Analytics, Algorithms, XML for Analysis (XMLA), API Integration, Dashboard Design, Web Analytics, BI Reports, Neural Networks, Data Cleansing, Datasets, ETL Tools, Data Build Tool (dbt), Data, Fivetran, Microsoft Azure, Time Series, Financial Modeling, Time Series Analysis, Diffusion Models, Variational Autoencoders, MLM, Data Reporting, Finance, Azure Data Factory, Google Data Studio, Vertex, Artificial Intelligence (AI), Consulting, GPT, Generative Pre-trained Transformers (GPT), Azure Data Lake

2021 - 2022

Master's Degree in Artificial Intelligence, Big Data, and Visual Analytics

International University of La Rioja - La Rioja, Spain

JANUARY 2023 - JANUARY 2025

Google Cloud Professional Machine Learning Engineer

Google Cloud

JANUARY 2023 - JANUARY 2026

AWS Machine Learning Specialty

Amazon Web Services

NOVEMBER 2022 - NOVEMBER 2023

Power BI Data Analyst Associate

Microsoft

APRIL 2022 - PRESENT

Data Science and Big Data: Data-driven Decisions

MIT xPRO

MARCH 2022 - PRESENT

IBM Data Science Specialization

IBM

Collaboration That Works

How to Work with Toptal

Toptal matches you directly with global industry experts from our network in hours—not weeks or months.

1

Share your needs

Discuss your requirements and refine your scope in a call with a Toptal domain expert.
2

Choose your talent

Get a short list of expertly matched talent within 24 hours to review, interview, and choose from.
3

Start your risk-free talent trial

Work with your chosen talent on a trial basis for up to two weeks. Pay only if you decide to hire them.

Top talent is in high demand.

Start hiring