Marcos Heidemann Email & Phone Number | I currently serve as the Data Science Team Lead for a team of over 30 people, guiding them in best practices, and innovative and efficient ways to solve day-to-day problems. Led Projects: Route optimization solution using Traveling Salesman Problem concepts Targeted marketing solution using geospatial data Building an informational dashboard from telemetry data of devices Identification of customer profiles within the company database from a socio-economic standpoint Contributed to the creation of a predictive model for the legal department Development of best practices and processes to improve the quality of the model lifecycle Leadership and architecture design for deploying an ML Ops pipeline Involved in creating models for energy product sales and improving customer monetization Strong personal interest in using machine learning techniques for geospatial remote sensing Advanced Technologies Used: Python for developing routing solutions and data analysis OR-Tools for route optimization Clustering techniques like K-means or DBSCAN for geospatial data segmentation and customer profile identification Neural Networks, specifically Convolutional Neural Networks, for telemetry data analysis Folium for geospatial data visualization Plotly for interactive data visualization Geopandas for geospatial data manipulation Geopy for geocoding and address manipulation Dash for creating interactive dashboards Ray for distributed application scaling and performance optimization CUDA for data processing acceleration with GPUs Automated testing tools to ensure code quality Agile methodologies for project management and continuous development process improvement ML Ops platforms to ensure the scalability and availability of produced models Optimization algorithms like ALNS, genetic algorithms, etc. Data visualization tools for presenting results and insights I have advanced knowledge in handling large datasets and accelerating analyses and training using multiprocessing techniques. My goal is to continue contributing innovative and efficient solutions to the company, generating significant results in terms of efficiency, accuracy, and ROI.

Marcos Heidemann

I currently serve as the Data Science Team Lead for a team of over 30 people, guiding them in best p...
Petrópolis, Rio De Janeiro, Brazil

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Marcos Heidemann’s Email marcos.heidemann@oi.net.br

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Marcos Heidemann’s Location Petrópolis, Rio De Janeiro, Brazil

Marcos Heidemann’s Current Industry Nops Io

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Work Experience

Nops Io

Principal Data Scientist

2023-11-01 00:00:00 - Present

Oi

Executive Consultant In Data Science

2022-01-01 00:00:00 - 2023-11-01 00:00:00

Lead Data Scientist

2017-06-01 00:00:00 - 2022-01-01 00:00:00

Modulo Security Solutions

Solutions Consultant

2014-01-01 00:00:00 - 2017-05-01 00:00:00

Citel

Senior Bi Analyst

2013-03-01 00:00:00 - 2014-01-01 00:00:00

Atex

Analyst

2011-10-01 00:00:00 - 2012-10-01 00:00:00

Accenture

Analyst

2008-07-01 00:00:00 - 2011-07-01 00:00:00

Microsoft Innovation Center

Bolsista

2007-03-01 00:00:00 - 2007-11-01 00:00:00

Skills

No Skills Available

Languages

No Languages Available

FAQ About Marcos Heidemann

Marcos Heidemann is located at
Petrópolis, Rio De Janeiro, Brazil

Marcos Heidemann is a I currently serve as the Data Science Team Lead for a team of over 30 people, guiding them in best practices, and innovative and efficient ways to solve day-to-day problems. Led Projects: Route optimization solution using Traveling Salesman Problem concepts Targeted marketing solution using geospatial data Building an informational dashboard from telemetry data of devices Identification of customer profiles within the company database from a socio-economic standpoint Contributed to the creation of a predictive model for the legal department Development of best practices and processes to improve the quality of the model lifecycle Leadership and architecture design for deploying an ML Ops pipeline Involved in creating models for energy product sales and improving customer monetization Strong personal interest in using machine learning techniques for geospatial remote sensing Advanced Technologies Used: Python for developing routing solutions and data analysis OR-Tools for route optimization Clustering techniques like K-means or DBSCAN for geospatial data segmentation and customer profile identification Neural Networks, specifically Convolutional Neural Networks, for telemetry data analysis Folium for geospatial data visualization Plotly for interactive data visualization Geopandas for geospatial data manipulation Geopy for geocoding and address manipulation Dash for creating interactive dashboards Ray for distributed application scaling and performance optimization CUDA for data processing acceleration with GPUs Automated testing tools to ensure code quality Agile methodologies for project management and continuous development process improvement ML Ops platforms to ensure the scalability and availability of produced models Optimization algorithms like ALNS, genetic algorithms, etc. Data visualization tools for presenting results and insights I have advanced knowledge in handling large datasets and accelerating analyses and training using multiprocessing techniques. My goal is to continue contributing innovative and efficient solutions to the company, generating significant results in terms of efficiency, accuracy, and ROI.

Marcos Heidemann currently works in the Nops Io |

No Languages Available

Marcos Heidemann has prior
experience in the following industries:
Oi | Lead Data Scientist | Modulo Security Solutions | Citel | Atex | Accenture | Microsoft Innovation Center

Marcos Heidemann has the following professional experience:
Nops Io | Oi | Lead Data Scientist | Modulo Security Solutions | Citel | Atex | Accenture | Microsoft Innovation Center