Ryan Dawson

Data Scientist

https://www.opentalent.in/ryan-dawson

thoughtworks

Member since June 24, 2026

Key Strengths

Exposure to various MLOps platforms (SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow) indicates a broad understanding of the data science ecosystem.
Experience with Python and R for machine learning exercises demonstrates foundational knowledge in key data science programming languages.
Familiarity with Kubernetes concepts (secrets, configmaps, namespaces) is valuable for deploying and managing data science workloads.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects show a strong inclination towards personal learning and exploration, particularly in MLOps, data platforms, and Kubernetes. This self-driven learning approach could be a good cultural fit for an innovative environment. However, the project descriptions are brief, making it difficult to fully assess the depth of engagement or collaborative potential. The current role as 'Data Scientist' at Thoughtworks aligns with the target role, but without further details on responsibilities or team interactions, a comprehensive cultural fit assessment is challenging.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insight.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

data-platforms-tools

March 9, 2022 – March 9, 2022

Guide to data platforms and tools

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mlops-platforms

October 1, 2021 – November 10, 2022

Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...

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environment-ferretmaze-staging

May 31, 2018 – November 1, 2018

environment-ferretmaze-staging — repository

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k8snamespaces-startrek

May 4, 2018 – May 11, 2018

k8s namespaces illustration

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secrets-treasurehunt

April 14, 2018 – April 25, 2018

Game to illustrate Kubernetes secrets

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configmaps-transformers

March 31, 2018 – April 8, 2018

Demo using shared ConfigMaps for Java Apps

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configserver

March 24, 2018 – March 24, 2018

configserver — repository

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minions

March 3, 2018 – March 4, 2018

Minions for minikube - a demo of kubernetes features

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poc-activiti-jhipster

October 26, 2017 – October 27, 2017

A demo with JHipster, Keycloak and Activiti

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UdemyMachineLearningAtoZPythonAndR

January 25, 2017 – February 6, 2017

Exercises and examples from Udemy MachineLearningA-Z course together with my notes.

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Key Strengths

Exposure to various MLOps platforms (SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow) indicates a broad understanding of the data science ecosystem.
Experience with Python and R for machine learning exercises demonstrates foundational knowledge in key data science programming languages.
Familiarity with Kubernetes concepts (secrets, configmaps, namespaces) is valuable for deploying and managing data science workloads.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insight.

Ryan Dawson

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit