Nestor Yuri Sanchez Guadarrama, Developer in Edinburgh, United Kingdom
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Nestor Yuri Sanchez Guadarrama

Verified Expert  in Engineering

Data Scientist and Software Developer

Edinburgh, United Kingdom
Toptal Member Since
March 23, 2022

Nestor has a solid academic background in machine learning and industry experience as a software engineer and data scientist. He built a production-level Python package for power system adequacy modeling used by researchers at the Alan Turing Institute, a GCP-based end-to-end ML pipeline for generative deep learning models, and ML-based products to understand the impact of PR campaigns. Nestor enjoys staying up-to-date with the latest technologies in the data science and MLOps spaces.


Amazon Web Services (AWS), Python, Linux, Amazon SageMaker
Python, Bash, SQL, Python 3
The Alan Turing Institue
Python, C, Statistics, Pandas, NumPy, RStudio, Project Management




Preferred Environment

Linux, Python, Google Cloud Platform (GCP), R

The most amazing...

...model I have worked on enabled a 4% throughput increase in a high-value production process.

Work Experience

Data Scientist

2023 - PRESENT
  • Led initiatives for tooling and code quality standards across the data science team.
  • Pushed model performance above the threshold for shadow deployment at the factory floor for two different use cases.
  • Quantified the potential return on investment (ROI) for machine learning (ML) use cases in predictive quality to obtain buy-in from fab managers.
Technologies: Amazon Web Services (AWS), Python, Linux, Amazon SageMaker

Back-end Engineer

2022 - PRESENT
  • Maintained the back-end codebase and ETL pipelines continuously using Python and Bash.
  • Implemented new features and optimized ETL pipelines.
  • Created documentation for the legacy codebase and swapped out old or deprecated libraries.
Technologies: Python, Bash, SQL, Python 3

Research Software Engineering Consultant

2022 - 2022
The Alan Turing Institue
  • Produced a production-level Python package for power system adequacy modeling intended to be used by researchers on projects outside the scope of my Ph.D.
  • Engaged with researchers to familiarize them with the package functionality.
  • Collaborated on developing a decision support system for risk management and capacity procurement in the context of Great Britain's power system.
Technologies: Python, C, Statistics, Pandas, NumPy, RStudio, Project Management

Academic Consultant

2021 - 2021
National Grid
  • Produced an analysis of near-term security of supply risks for the power grid under different future scenarios.
  • Engaged with stakeholders and other academic consultants to understand their needs in terms of software and modeling.
  • Produced a solid codebase and ensured a solid and reproducible analysis through good engineering practices.
Technologies: R, Data Science, Statistics, Data Visualization, RStudio

ML Engineering Consultant

2018 - 2018
Wella Online
  • Prototyped a new data service in the form of an ML-based student failure prediction pipeline.
  • Engaged with the client and product teams frequently to incorporate their feedback into the project.
  • Deployed on AWS as a RESTful API using Python's Falcon and a MongoDB back end.
Technologies: Python, MongoDB, Amazon Web Services (AWS), Data Science, Machine Learning, Pandas, NumPy, Scikit-learn, Project Management, Python 3

Software Developer

2015 - 2017
  • Quantified the impact of marketing campaigns using network models and NLP.
  • Created ML models for demographic feature inference of Twitter users.
  • Collaborated directly with clients to design ML-backed dashboards for real-time audience segmentation.
Technologies: Python, R, Spark, Scala, Amazon Web Services (AWS), Bash, Data Science, Statistical Data Analysis, Statistics, Machine Learning, Data Visualization, Data Analysis, Generative Pre-trained Transformers (GPT), GPT, Natural Language Processing (NLP), Data Analytics, Scikit-learn, RStudio, RStudio Shiny, Project Management, Data Extraction, Python 3, SQL

Data Scientist

2015 - 2015
  • Tested statistical hypotheses to better understand the customers.
  • Produced the methodology for a weekly KPI forecast report intended for executive-level management.
  • Assisted in improving the quality of credit scoring models.
Technologies: R, Data Science, Statistical Data Analysis, Statistics, Machine Learning, Data Visualization, Data Analysis, Data Analytics

Generative Models for Typefaces
A Python package implementing a GCP-based end-to-end machine learning pipeline for generative deep learning models using Typeface data. It uses Beam for data preprocessing, TensorFlow for model training, and MLFlow for experiment tracking.

Production-level Code for Power System Adequacy Modeling
A Python package implementing parametric extreme value models and optimized functionality for power system adequacy assessment. The package will be used by researchers at the Alan Turing Institute for various projects involving energy adequacy risks for future climate scenarios.

Bootstrapping a Kubernetes Cluster on EC2 from Scratch
This repository uses GNU Make, Ansible, Terraform, and Python to bootstrap a highly available Kubernetes cluster on EC2 from the ground up. It is meant as a testing ground for some DevOps technologies.


Python, R, SQL, Python 3, Bash, C, Scala


Pandas, NumPy, Scikit-learn, TensorFlow


Data Science, Parallel Programming, CRISP-DM


RStudio, Linux, Google Cloud Platform (GCP), Kubernetes, Amazon Web Services (AWS)

Industry Expertise

Project Management


Statistics, Mathematics, Machine Learning, Data Visualization, Statistical Data Analysis, Data Analysis, Data Analytics, Data Extraction, Research, Software Engineering, Natural Language Processing (NLP), Time Series Analysis, Forecasting, GPT, Generative Pre-trained Transformers (GPT), IT Project Management, Distributed Systems, Big Data, Big Data Architecture, Cloud Computing, Data Engineering


RStudio Shiny, Spark


Apache Beam, Ansible, Terraform, GNU Make, Amazon SageMaker



2019 - 2022

Ph.D. in Statistics

University of Edinburgh - Edinburgh, UK

2018 - 2019

Master's Degree in High Performance Computing

University of Edinburgh - Edinburgh, Scotland

2010 - 2014

Bachelor's Degree in Informatics and Applied Mathematics

Mexico Autonomous Institute of Technology - Mexico City, Mexico


Professional Data Engineer

Google Cloud


Structuring Machine Learning Projects


Collaboration That Works

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