Pedro P. Sanchez

Data Scientist

https://talent.gravityer.com/pedro-p-sanchez

AI at Hike Medical. AI PhD.

University of Edinburgh

Key Strengths

Strong foundational experience in Python for data science and machine learning, particularly in deep learning and generative models.
Extensive project experience in medical imaging (3D segmentation, chest X-ray analysis) and causal discovery, demonstrating specialized domain knowledge.
Proficiency with advanced deep learning frameworks and concepts (Diffusion Models, Latent Diffusion Models, Adversarial Networks, MONAI Generative Models).

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are heavily concentrated in research-oriented deep learning and medical imaging, which aligns well with a Data Scientist role focused on advanced model development and scientific inquiry. However, the lack of diverse project types (e.g., deployment, MLOps, business intelligence, traditional statistical modeling) suggests a potentially narrow focus, which might impact adaptability to broader data science challenges. The single listed professional experience as 'Data Scientist' at a university, with a future start date, provides limited insight into real-world team collaboration or industry practices.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback are available.

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Assessing your cultural and operational fit

Projects

one_sample_memorisation

February 15, 2023 – February 16, 2023

one_sample_memorisation — GitHub repository

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generative_chestxray

February 4, 2023 – July 5, 2023

Repository to train Latent Diffusion Models on Chest X-ray data (MIMIC-CXR) using MONAI Generative Models

View Project

DiffAN

October 12, 2022 – October 12, 2022

Diffusion Models for Causal Discovery

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Diff-SCM

February 20, 2022 – June 7, 2023

Code for Diff-SCM paper

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Diff-SCM

February 7, 2022 – July 29, 2022

Code for Diff-SCM paper

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adni_preprocessing

June 14, 2021 – June 13, 2024

ADNI t1-weighted MRI preprocessing

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tsaftarislab.github.io

October 14, 2019 – Present

Github Pages for vios group, forked from mmistakes/minimal-mistakes

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Segmentation-Adversarial_Networks

December 8, 2018 – December 14, 2018

Segmentation of the cerebrovascular system using deep learning and adversarial training

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Segmentation_3D_DeepLearning

September 20, 2018 – January 6, 2020

Segmentation_3D_DeepLearning — GitHub repository

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DeepSeg3D

May 24, 2018 – July 6, 2023

Neural network toolkit for 3D image segmentation

View Project

Key Strengths

Strong foundational experience in Python for data science and machine learning, particularly in deep learning and generative models.
Extensive project experience in medical imaging (3D segmentation, chest X-ray analysis) and causal discovery, demonstrating specialized domain knowledge.
Proficiency with advanced deep learning frameworks and concepts (Diffusion Models, Latent Diffusion Models, Adversarial Networks, MONAI Generative Models).

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback are available.

Pedro P. Sanchez

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit