Ivan González Schulten

• Programming solutions for Services on AWS, such as Redshift, S3, Lambda, EMR, EC2, Aurora, Athena, Step Function, DynamoDB
• Solutions and orchestration created with the aforementioned services
• Dedication and guidance for cell group to solutions integration, also unit testing and QA
• Use of Python 2.6+, Pyspark, Scala and Dax Languages, Java where maven was used as compiler, also interaction with DB like Oracle and Mysql through ssh tunneling with Putty where linux was installed (Azure)
• The Company uses agile and scrum methodology, using tools of platforms like Atlassian
• We created a whole flux from Sap to models which were shown on visualizations on a web application
• We made a emigration from Azure to AWS, using all similar Services which aws did offer.

• Giving Support to the Citi Bank in the US in Technology Fields, such as:
• Arcadia
• Pyspark
• Tableau
• Kafka
• Scala/Spark
• Relational DBs like Cassandra and PostgreSQL
• As a team we created a streaming program, which did capture all the clicks and views of a normal User and transformed the data in valuable information for the team at the Citibank

• I was hired as support for the Solution team, to generate data integrations and automated ingests through the platform
• Cloudera, using Sqoop, Hive, Impala, Spark, and Kafka
• I was also asked to train the team in the use of the services of
• Cloudera
• Used Pyspark, also creating Lambdas interacting with the other services of AWS, like DynamoDB, Redshift, Athena and S3 for modeling and creating outputs in the Data Warehouse.

• I was hired for the fulfillment of a ML modeling project
• Of Frauds and automatic licensing, using Pyspark on Zeppelin (EMR), Java,
• Scala, Glue and showing the business logic on Tableau
• I implemented for automatic viewing, data integration, ingest and debugging, and then leaving WF running through more than 300 created variables was able to automatically endorse the licenses until 30% per month
• Using Pipeline iterations of a Tuned Random Forest and Kmeans , with automation of the Threshold so that the cost of error does not exceed the cost of error for the staff who were in charge of reviewing the licenses manually (AWS)

• Technology solutions company - Implementation of Machine Learning models (knn, Random Forest, tree decisions, bayesian, Svm), AI, Forecasting (exponential smoothing, holt-Winters, Arma, Arimax), presentations on PowerBI, automated, creation of mathematical algorithms for the calculation of indicators for E-commerce clients
• Solutions and creation of new automated algorithms and supervised and unsupervised learning for companies, Based on programming languages
  
  such as: Python, Java, Autoit, html, Dax among others
• Use of Hadoop Cloudera for handling large amounts of data (Big Data) and processing it to create a data flow between SQL servers and then for its automated ingestion to PowerBI with a gateway
• Sqoop, Hive, Spark, Scala, Pyspark, Impala, ssh tunneling Unix -Use of AWS and Cloudera, to manage ingest, manipulate algorithms and machine learning models with Spark using the apis Python and Scala
• Streaming with Spark and Kafka, structuring data with Hive and Impala, creating Spark applications such as Workflows for technological solutions for different companies and complementing Software's and applications created by Anticipa
• Cloudera platform support
• Also worked with MariaDB, Mysql, SQL Server and NoSQL DB like Mongo and Cassandra
• Use of Atlassian tools like Jira, Confluence and Bitbucket.

Academic Professor of Financial Mathematics and Mathematical Tools for Electrical Engineers

• Creation of Macros in Python and Excel Creation and manipulation of structured databases in Sql to find solutions of data inefficiency and software developer in Python, Java
• Creation of reports in PowerBI with interaction in R and Dax
• Automation of systems via Bots in Autoit, C # and use of Pentaho
• Statistical analysis of workers creating RFM and K-Means clustering models, to find inefficiency groups of workers, Using the AWS platform with Spark-Glue, in Pyspark and other Jobs in Spark Scala.

• I was in charge of automating models and graphs online with SQL, Python and Pentaho Integration on AWS, so that statistical information for clients was automatically updated in PowerBI
• Financial Analysis through Machine Learning models (Random Forest, Random Forest classification models, KNN) created with Spark ML libraries in Scala and Pyspark (Cloudera)

• Creation of statistical models with databases in Excel and SQL to create probabilistic reports of when fraud or internal theft could occur in the company, using R and Python programming languages
  
  to be presented in an automated way in PowerBI and using Pentaho for reports sent via email with AWS S3, Emr, Athena and Glue services

• Germany's largest Polymer Research Institution
• Creation of macros in Python, C and Spec X-Ray for MPIP
• Functional organization of the procedure of experiments
• Scientific control
• Implementation of Machine Learning algorithms for image processing and logical and exponential regressions, in Python, Pyspark and R on the Cloudera Data Science Workbench platform, making large ingests of image data, the servers were physical and therefore required constant maintenance And control.

• Control of attracting new clients
• Generation of Django forms in Python, for structuring the order of deliveries
• Working with Relational DB like MySQL and SQL Server, in order to connect the forms information - Presentations in PowerBI, creation of forms in Django (Python), for the correct operation of Deliveries, Data ingestion through AWS (SparkSQL)
• Automation.