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I am a Data Scientist with over 15 years of experience turning data into actionable insights and accurate forecasts. I combine statistical rigour and data engineering with machine learning algorithms to design models that balance accuracy, interpretability and computational efficiency. I minimise project risk and optimise business impact through data-driven decision-making and model deployment. Across financial services, mobility, healthcare and wearables, I have delivered credit risk scorecards, automated model monitoring, GPS data quality evaluations, and predictive analytics that translate complex data into practical business value. I enjoy collaborating with cross-functional teams to turn data into strategic actions and measurable outcomes.…I am a Data Scientist with over 15 years of experience turning data into actionable insights and accurate forecasts. I combine statistical rigour and data engineering with machine learning algorithms to design models that balance accuracy, interpretability and computational efficiency. I minimise project risk and optimise business impact through data-driven decision-making and model deployment. Across financial services, mobility, healthcare and wearables, I have delivered credit risk scorecards, automated model monitoring, GPS data quality evaluations, and predictive analytics that translate complex data into practical business value. I enjoy collaborating with cross-functional teams to turn data into strategic actions and measurable outcomes.

Miguel A. G. Belmonte

Data Scientist, Data Analyst, AI Developer, +2

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I am a Data Scientist with over 15 years of experience turning data into actionable insights and accurate forecasts. I combine statistical rigour and data engineering with machine learning algorithms to design models that balance accuracy, interpretability and computational efficiency. I minimise project risk and optimise business impact through data-driven decision-making and model deployment. Across financial services, mobility, healthcare and wearables, I have delivered credit risk scorecards, automated model monitoring, GPS data quality evaluations, and predictive analytics that translate complex data into practical business value. I enjoy collaborating with cross-functional teams to turn data into strategic actions and measurable outcomes.…I am a Data Scientist with over 15 years of experience turning data into actionable insights and accurate forecasts. I combine statistical rigour and data engineering with machine learning algorithms to design models that balance accuracy, interpretability and computational efficiency. I minimise project risk and optimise business impact through data-driven decision-making and model deployment. Across financial services, mobility, healthcare and wearables, I have delivered credit risk scorecards, automated model monitoring, GPS data quality evaluations, and predictive analytics that translate complex data into practical business value. I enjoy collaborating with cross-functional teams to turn data into strategic actions and measurable outcomes.

Available to hire

I am a Data Scientist with over 15 years of experience turning data into actionable insights and accurate forecasts. I combine statistical rigour and data engineering with machine learning algorithms to design models that balance accuracy, interpretability and computational efficiency. I minimise project risk and optimise business impact through data-driven decision-making and model deployment.

Across financial services, mobility, healthcare and wearables, I have delivered credit risk scorecards, automated model monitoring, GPS data quality evaluations, and predictive analytics that translate complex data into practical business value. I enjoy collaborating with cross-functional teams to turn data into strategic actions and measurable outcomes.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Remote Machine Learning Mentor at Universitat de Barcelona IL3

January 1, 2024 - January 1, 2025

Support professional learners applying statistical and machine learning methods to empirical datasets; translate theory into real-world analytical practice. Cover topics including Maximum Likelihood, gradient descent, statistical inference, regression analysis, neural networks and decision trees with practical Python implementation; Exploratory Data Analysis in R and feature engineering in Python; model generalization, bias-variance trade-off; collaborate with learners to adopt predictive modelling, data visualization, and performance metrics; reinforce communication skills.

Senior Data Scientist at Intrum Global Technologies – Centre of Excellence, Spain

January 1, 2022 - January 1, 2024

Credit Risk Scorecard Development: Benchmarked monotonic Logistic Regression vs Random Forest and Gradient Boosting to balance interpretability and predictive power. Model Monitoring Library: modular Python monitoring system with automated checks for predictor stability, model usage, performance and business impact, visualised via an interactive Streamlit dashboard. Automation & Deployment: Apache Airflow pipelines for automated model retraining, testing and reporting. Data Engineering & Feature Selection: data extraction and cleaning with SQL and dbt.

Senior Data Scientist at INRIX UK

January 1, 2021 - January 1, 2022

GPS Data Quality: Developed a Hidden Markov Model map-matching algorithm; modeled emission/transition probabilities with Gaussian kernels; designed a normalized GPS quality index integrating speed, turning angle and motion direction. On-Street Parking Prediction: Implemented CatBoost to predict parking availability with high-cardinality categorical variables; validated predictive accuracy and calibration with Brier score and log-loss. Data extraction & Feature Selection: AWS data extraction with PySpark; MRMR feature selection to optimize model performance.

Research Associate at Wearable Clinic, University of Manchester

January 1, 2019 - January 1, 2021

Human Activity Recognition: Applied LSTM and CNN models to labelled accelerometer data from wrist-worn devices for behavioural pattern recognition. Behavioural Phenotyping: Developed a sequential Gaussian Mixture Bayesian classifier to phenotype 100,000+ unlabelled UK Biobank accelerometer records, enabling visualization of switching instances in activity.

Research Associate at University of Manchester

January 1, 2016 - January 1, 2019

Antibiotic Prescribing Optimisation: Contributed to a learning health system analysing prescribing rates with General Linear and General Additive models; visualized variance explained with stacked bar plots. Data Pipeline: Built a complete data science workflow with PostgreSQL, R and ggplot2; delivered an interactive RShiny dashboard for actionable insights. Collaboration & Project Management: Version-controlled code in GitLab and followed an agile Kanban workflow to ensure transparent, iterative development.

Knowledge Transfer Partnership Associate at Business Safety Systems, Ltd

January 1, 2013 - January 1, 2016

Sickness Absence Prediction: Developed statistical modelling software to help organisations predict, mitigate and reduce unplanned employee absence. Technology Implementation: Built a fully open-source technology stack using PostgreSQL and R. Data Analysis & Modelling: Analysed proprietary absence dataset under NDA to design multivariate Logistic Regression and Survival Models. Stakeholder Communication: Presented complex quantitative insights to non-specialist audiences (CIPD, DWP).

Research Fellow at University of Strathclyde

January 1, 2010 - January 1, 2013

Macroeconomic Forecasting: Applied Bayesian simulation-based methods to forecast EU employment, GDP and inflation during volatile periods. Advanced Modelling: Finite Mixture Models with Bayesian Lasso regularisation to improve predictive stability. Research Impact: Produced robust forecasts for time-varying parameter models; Bayesian Lasso allowed coefficients to be time-varying, constant or shrunk to zero.