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Andres Palechor

Research Assistant
Habilidades
(Autoevaluación)
Python programming 90%
Python(pandas, matplotlib) 90%
Excel 90%
Pytorch 80%
Powerbi 80%
SQL 80%
Git 80%
Machine learning 80%
Data analytics 80%
Statistics 70%
Idiomas
English:
  • Fala
    70%
  • Leitura
    70%
  • Escrevendo
    70%
Spanish:
  • Escrevendo
    70%
  • Leitura
    70%
  • Fala
    70%
German:
  • Leitura
    70%
Perfil profesional

Experiencia laboral

Research Assistant
grupo de inteligencia artificial y machine learning, universidad de zúrich | Enero 2022 - Enero 2023 (1 year)
Habilidades utilizadas

* Design and implementation of ML pipelines in novel (adversarial) training methods for deep networks (ResNet varieties) in image classification. * Optimization of image processing pipelines using Nvidia Dali, significantly reducing time preprocessing and efficiently using GPUs resources.

Logro principal

* Development of an open-source training and evaluation package in Python for open-set classification using standard libraries (Pandas, Numpy, Scikit-learn, SciPy) and Pytorch.

Slas Process And Transition Engineer
e2e technology solutions | Enero 2015 - Enero 2019 (4 years)
Habilidades utilizadas

* Gathering data from various sources such as ODBC, APIs, and websites, and creating data models and visualizations in Power BI to track KPIs and ensure SLAs are met. * Perform SLA GAP analysis, KPI and SLO of standard offers (LAN, WLAN, MRS, AVPN) for customized requirements of key clients. * Coordination of multidisciplinary teams and stakeholders to implement customized SLA solutions for key AT&T clients.

Logro principal

* Implementation of data analysis pipelines for the evaluation of financial and technical risks of SLA solutions for key customer accounts in connectivity solutions

Data Analyst
e2e technology solutions | Enero 2014 - Enero 2015 (1 year)
Habilidades utilizadas

* Development of risk and financial impact models of customized SLA solutions based on technical architecture data and network performance, mainly through regressions, random forests and clustering algorithms such as DBScan.

Logro principal

* Construction of data models (DAX) and design of exhaustive dashboards (in PowerBI) for the visualization of critical business processes related to the technological infrastructure.

Formación académica
Computer Science
University of zurich | Master
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