Nicolas Perez can be reached at nperez@stregisnyc.com for any inquiries. His address is 2 East 55th Street, New York City, USA. You can contact him directly at +1-212-753-4500.
- Proficient in advanced statistical analysis and machine learning techniques to derive actionable insights from complex datasets, driving data-driven decision-making within the organization.
- Skilled in programming languages such as Python and R for data manipulation and visualization, with a proven track record of developing predictive models that optimize business processes and enhance performance.
- Title: "Predictive Modeling of Customer Churn in Telecommunication Industry"
  Journal: International Journal of Data Science
  Year: 2015

- Title: "Anomaly Detection in Network Traffic Using Machine Learning Techniques"
  Conference: IEEE Big Data Symposium
  Year: 2016

- Title: "Natural Language Processing for Sentiment Analysis in Social Media Posts"
  Journal: Journal of Artificial Intelligence Research
  Year: 2017

- Title: "Deep Learning Approaches for Image Recognition in Healthcare Applications"
  Conference: ACM Conference on Health Informatics
  Year: 2018

- Title: "Time Series Forecasting with Recurrent Neural Networks"
  Journal: Neural Computing and Applications
  Year: 2019
- Proficient in advanced statistical analysis and machine learning techniques to derive actionable insights from complex datasets, driving data-driven decision-making within the organization.
- Skilled in programming languages such as Python and R for data manipulation and visualization, with a proven track record of developing predictive models that optimize business processes and enhance performance.
Nicolas Perez can be reached at nperez@stregisnyc.com for any inquiries. His address is 2 East 55th Street, New York City, USA. You can contact him directly at +1-212-753-4500.
- Title: "Predictive Modeling of Customer Churn in Telecommunication Industry"
  Journal: International Journal of Data Science
  Year: 2015

- Title: "Anomaly Detection in Network Traffic Using Machine Learning Techniques"
  Conference: IEEE Big Data Symposium
  Year: 2016

- Title: "Natural Language Processing for Sentiment Analysis in Social Media Posts"
  Journal: Journal of Artificial Intelligence Research
  Year: 2017

- Title: "Deep Learning Approaches for Image Recognition in Healthcare Applications"
  Conference: ACM Conference on Health Informatics
  Year: 2018

- Title: "Time Series Forecasting with Recurrent Neural Networks"
  Journal: Neural Computing and Applications
  Year: 2019
