Hello!

I am Simon Rendon Arango

Personal illustration

I build intelligent systems that turn messy data into clarity, combining machine learning, software design, and a bit of curiosity-driven engineering.

London, UK
Roles
ML Engineer · Full‑Stack
Location
London · Hybrid
Connect
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About Me

Software and Machine Learning Engineer

Hi, I’m Simon Rendon Arango, a Software and Machine Learning Engineer passionate about building intelligent systems that turn complex data into actionable insights. I hold an MSc in Computing (Software Engineering) from Imperial College London and a BSc in Systems and Computing Engineering from Universidad de los Andes. My professional journey spans startups and fintech, where I’ve designed AI-driven KPI extraction modules, developed scalable backend services, and built user-facing products at companies like Untap, Glamper, and Nequi (Bancolombia).
I’m also a curious creator, constantly exploring new technologies and side projects at the intersection of AI, data, and design. I thrive in fast-paced, collaborative environments where ambitious ideas meet rigorous execution — and I’m always looking for opportunities to push the boundaries of what’s possible with software and machine learning.

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Experience

Professional Experience

Untap logo

Junior Software Engineer @ Untap

Nov 2024 – Present
Outcomes
90%+ KPI extraction accuracyAutomated testing coverage increasedFaster insight retrieval via Gemini
Tech Stack
ReactJavaScriptJavaVertexGeminiGCP
Impact
  • Developed and maintained software for private equity investment management using Java, Python, and JavaScript
  • Integrated Google Gemini for intelligent extraction and summarization of business‑critical information
  • Built an LLM‑based system to extract KPIs from financial reports with 90%+ accuracy
  • Implemented automated testing to ensure code quality, reliability, and maintainability across the development lifecycle
Glamper logo

Software Engineer @ Glamper

Mar 2023 – Sep 2023
Outcomes
LLM‑powered personalizationServerless backend on AWSImproved UX & engagement
Tech Stack
VueJavaScriptNuxtPythonAWS
Impact
  • Developed and maintained the Glamper web application using Vue.js and Nuxt.js, enhancing user experience and functionality
  • Integrated LLMs to provide personalized travel recommendations and improve customer engagement
  • Participated in code reviews and implemented best practices to ensure high-quality code and maintainability
  • Created a serverless backend using AWS Lambda and API Gateway to handle user requests and data processing
Bancolombia logo

Intern Software Engineer @ Bancolombia

Jul 2021 - Jan 2022
Outcomes
Automated incident trackingReduced deployment overhead
Tech Stack
PythonJavaScriptAWS
Impact
  • Developed internal AWS–Jira connectors to automate incident tracking, improving response time for infrastructure tickets.
  • Automated several cloud migration workflows, significantly reducing deployment overhead as Bancolombia transitioned to AWS.
Skills Dashboard

Core Skills & Technical Expertise

Frontend

React logo
ReactExpert
TypeScriptExpert
JavaScriptExpert
VueProficient
Nuxt.jsProficient
Tailwind CSSExpert
Framer MotionAdvanced
shadcn/uiAdvanced

Backend & Cloud

Node.jsExpert
ExpressAdvanced
PythonExpert
JavaAdvanced
C++Proficient
GCPAdvanced
AWSAdvanced
DockerAdvanced
Next.jsExpert

Machine Learning & Data

TensorFlowAdvanced
Scikit-learnAdvanced
PandasExpert
NumPyExpert
PyTorchProficient
JupyterExpert
GeminiProficient
OpenAIProficient
LLMsAdvanced
Data VisualizationAdvanced

Other / DevOps

CI/CDAdvanced
HPCProficient
DesignAdvanced
GitExpert
GitHubExpert
GitLabAdvanced
Projects

Projects Worked On

Machine Learning – Predicting Formula 1 Results

Machine Learning – Predicting Formula 1 Results

Undergraduate thesis predicting race winners across seasons with ~93% accuracy.

93%+ accuracy in winner predictionPodium probability distribution modelingModel explainability (SHAP) for trustValidated against betting odds (profitable)
PythonTensorFlowScikit-learnPandas
Open Source
Performance Regression Detection in HPC (Nektar++)

Performance Regression Detection in HPC (Nektar++)

Master’s thesis: Deep learning anomaly detection on performance counters integrated into CI.

Regression triage time cut from days to <2 hoursAutomated anomaly detection in CICounter attribution for root cause analysis
PythonTensorFlowScikit-learnPandasNumPyHPCGitLab CIDeep LearningOpen Source
UNTAP – Extractive AI Assistant

UNTAP – Extractive AI Assistant

LLM-based system that extractys KPIs, targets and metrics from financial documents.

Reduced analyst data extraction time by 70%+Improved accuracy of extracted KPIsScalable to large document volumes
JavaGCPReactLLM
Interactive Career Graph

Interactive Career Graph

Explorable knowledge graph of roles, education, tech & projects with dynamic layouts.

Communicates experience as a knowledge graphMultiple dynamic layouts and export optionsAccessible and themable
TypeScriptReactFramer MotionData VisState Encoding
ProjectWIP

Live Football Model (LFM)

Real-time probabilities, an embedding explorer, and a simulation toolkit that turns matches into living systems. I’m actively building it—come see the progress.

Live probabilitiesEmbedding explorerSimulation lab
State-of-the-art architecture
  • Streaming ingestion + feature store
  • Online inference with calibrated probabilities
  • Embeddings + vector search for similarity
  • Monte Carlo simulation engine
  • Real-time visualization layer
  • API-first design with SDKs
Visit LFMCurrently in progress
Model vs MarketLive · Embeddings · Sim
Education

Educational Background

Universidad de los Andes logo

Universidad de los Andes

Bachelor's Degree
Bachelor of Science in Systems and Computing Engineering
Bogotá, Colombia
Graduated:2023
Relevant Courses:
Data Structures, Algorithm design and analysis, Software Engineering, Mobile and Web Development, Software Architecture
Highlights:
  • Built a strong foundation in computer science, software development, and machine learning.
  • Completed hands-on projects including data analysis, algorithm design, and AI applications.
Imperial College London logo

Imperial College London

Master's Degree
Master of Science in Computing (Software Engineering)
London, United Kingdom
Graduated:Sep 2024
Relevant Courses:
Reinforcement Learning, Deep Learning, Software Engineering, Machine Learning, Natural Language Processing
Highlights:
  • Specialized in advanced software engineering principles, machine learning, and AI.
  • Conducted research and projects on scalable software systems and intelligent applications.
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Lets build something great

Reach out for roles, collaborations, or interesting problems.