I'm Diego,
a Senior Data
Scientist

Senior Data Scientist & ML Engineer | Ads-Tech, Recommenders, Supply Chain Optimization | $40M+ impact | Ex-Walmart, DHL, Huawei

Building robust, scalable ML systems that solve complex logistics and optimization challenges at Fortune 500 scale.

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Diego Hurtado
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IMPACT & ACHIEVEMENTS

Transforming Data into
Business Value

Proven track record of delivering enterprise-scale AI solutions that drive measurable business outcomes

Driving ROI with AI

Delivered $40M+ in revenue through AI Market Mix Modeling, achieving 10% CTR improvement and 30% supply chain efficiency gains across Fortune 500 enterprises.

💰Revenue Impact
$40M+
📈CTR Improvement
10%
Efficiency Gains
30%

From Pipelines to Production

End-to-end ML infrastructure architect specializing in scalable recommendation systems, GenAI solutions, and MLOps pipelines serving millions of users daily.

🔧ML Pipelines
15+
🚀Models Deployed
20+
👥Users Served
10M+

C-Level Strategy & Innovation

Bridging technical execution with strategic business outcomes, delivering data-driven insights that drive executive decision-making and digital transformation.

🎯Strategic Projects
25+
📊C-Suite Presentations
50+
💡Innovation Labs
5
⏱️
8+
Years Experience
💎
$40M+
Revenue Generated
🏢
Fortune 500
Enterprise Clients
🚀
20+
Production Models
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MY JOURNEY

Experience & Education

Professional Experience

Enero Group Ltd (OBMedia) logo
Dec 2024 – Present

Senior Data Scientist & Machine Learning Engineer

Enero Group Ltd (OBMedia)

High-volume ads pipeline+5% revenue per click; +8% advertiser ROI via personalization
  • Increased revenue per click by 5% by developing and integrating a Google Ads keyword recommender into a high-volume pipeline.
  • Architected and implemented an ETL pipeline on Google Cloud to research and analyze keyword search trends for media buyers, enabling actionable market insights.
  • Enhanced AdSense personalization using LLMs and Transformer-based embeddings (BERT), improving advertiser ROI by 8%.
  • Improved targeting relevance using embeddings + cosine similarity to strengthen relatedness measures and recommendation accuracy.
Walmart (#1 Fortune 500) logo
Jan 2024 – Dec 2024
11 months

Data Scientist (ML)

Walmart (#1 Fortune 500)

Large-scale e-commerce platform+10% CTR; +25% Recall@K for cross-sell recommendations
  • Boosted CTR by 10% through production deployment of ranking algorithms to optimize product relevance, leveraging billions of historical transactions across the catalog.
  • Increased Cross-Selling Recall@K by 25% by developing and deploying a recommendation system based on purchase behavior and digital engagement signals.
  • Built BERT-based item similarity models using product descriptions and interaction signals to improve semantic matching and recommendation quality.
DHL Supply Chain logo
Jan 2023 – Jan 2024
1 year

Data Scientist (ML)

DHL Supply Chain

USA & Mexico logistics operations30% operational efficiency; 50% faster payment processing; +5% backhaul identification
  • Improved operational efficiency by 30% through deployment of predictive analytics models for logistics optimization; reduced payment processing time by 50% across USA and Mexico shipments.
  • Boosted weekly backhaul identification by 5% by deploying XGBoost ETA and demand forecasting models (Prophet/XGBoost) feeding a linear programming optimizer.
Huawei logo
Jul 2020 – Jan 2023
2 years, 6 months

Data Scientist

Huawei

Telecom commercial & network planning$40M revenue impact; +39% targeting efficiency
  • Drove a US$40M increase in purchase orders by spearheading AI-powered market mix models to optimize marketing and site expansion strategy.
  • Boosted 5G user targeting efficiency by 39% through ML-driven offerings, pricing, and network planning—outperforming traditional campaigns by 14 percentage points.
  • Built a churn prediction model with geospatial analysis, producing churn probability lists and location-based recommendations that reduced churn by 5%.
Conacyt logo
Jul 2018 – Jul 2020
2 years

Data Scientist

Conacyt

Municipal operations & routing30% route distance reduction via ML + optimization
  • Achieved a 30% reduction in waste collection route distance using a hybrid optimization system combining XGBoost ETA prediction with routing heuristics and linear programming.
Baxter International Inc. (Fortune 500) logo
Mar 2016 – Jul 2018
2 years, 4 months

Data Analyst

Baxter International Inc. (Fortune 500)

Manufacturing operationsOperational visibility via IoT manufacturing dashboards
  • Developed manufacturing dashboards in SQL integrating IoT data (machines, sensors, labor) to support faster and more reliable production decisions.

Education

MSc in Optimization & Applied Computer Science

The National Autonomous University of Morelos

  • Focus on optimization and applied ML for real-world routing and planning problems.

BS in Computer Engineering

Polytechnic University of the State of Morelos

  • Strong foundation in algorithms, software engineering, and data structures.
Technical Expertise

Core Competencies

Deep expertise across the full ML lifecycle, from data engineering to production deployment

Hover over each skill category to see specific technologies

Machine Learning

95%
Scikit-learnXGBoostLightGBMCatBoostAutoMLFeature Engineering

Cloud/MLOps

90%
AWSDockerKubernetesTerraformMLflowCI/CD

Big Data

88%
Apache SparkPySparkDatabricksHadoopKafkaHive

Deep Learning

85%
PyTorchTensorFlowKerasHuggingFaceFastAIONNX

Data Engineering

92%
SQLPostgreSQLMongoDBRedisAirflowdbt

GenAI/LLM

87%
OpenAI APILangChainRAGVector DBsPrompt EngineeringFine-tuning
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TECHNICAL SKILLS

Technology Stack & Tools

💾

Languages & Databases

PythonSQLPySpark
🤖

ML/AI Libraries

PandasGeoPandasNumPyScikit-LearnTensorFlowSciPySpark MLlibDBTGitHubLLM
📊

Data Visualization

PowerBIPlotlyMatplotlibSeabornFlaskDashHTMLCSS
☁️

Big Data & Cloud

Google CloudBigQueryVertex AIDatabricksSnowflakeAirflowMLOps
🔧

Tools & DevOps

GitDockerKubernetesJupyter NotebooksVS Code
📈

ML & Marketing Analytics

Recommender SystemsTargetingSegmentationA/B TestingMMMChurn PredictionLTV Models
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ENGINEERING STRATEGY

Engineering Philosophy

Principles guiding my approach to building production ML systems at scale

Production > Perfection

I prioritize shipping simple, explainable baselines (like XGBoost) over complex deep learning models to establish rapid feedback loops. A model in production beats a perfect model on a laptop.

Deploy simple baselines first (XGBoost/Linear) before complex models

p99 latency < 100ms and 99.9% uptime SLA as non-negotiables

Horizontal scaling with Docker for production resilience

Data-Centric AI

I focus 80% of effort on data quality and pipeline reliability (dbt/Airflow) rather than hyperparameter tuning. Clean data beats clever algorithms.

Versioned datasets with Git integration

Automated data quality checks (Great Expectations/dbt tests)

Schema evolution with backward compatibility

Business Alignment

I translate 'Mean Squared Error' into 'Revenue Lift' to align engineering efforts with company OKRs.

A/B testing framework for measurable impact

Revenue attribution models for ML features

Executive dashboards with business KPIs

"The best code is the code that ships. The best model is the one that drives measurable business value."

— Diego Hurtado

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CASE STUDIES

Featured ML Systems & Case Studies

Production ML systems delivering measurable business outcomes at enterprise scale

Ads Keyword Recommender & LLM Personalization (OBMedia)

Ads Keyword Recommender & LLM Personalization (OBMedia)

PythonGCPBigQueryVertex AIBERTEmbeddingsCosine SimilarityETL

Ad performance depended on relevance and targeting quality in a high-volume pipeline, but keyword discovery and personalization lacked scalable, ML-driven tooling.

Business Impact

+5% RPC; +8% ROI

Scale

High-volume ads pipeline

Read Full Case Study
Ranking + Recommendations at Scale (Walmart)

Ranking + Recommendations at Scale (Walmart)

PySparkGCPBERTRankingRecommendation SystemsSQL

Large catalogs require relevance ranking and cross-sell recommendations that generalize across products and changing user behavior.

Business Impact

+10% CTR; +25% Recall@K

Scale

Billions of transactions

Read Full Case Study
Predictive Logistics + Optimization (DHL Supply Chain)

Predictive Logistics + Optimization (DHL Supply Chain)

PythonSQLXGBoostProphetLinear ProgrammingOperations Research

Logistics planning required better predictive signals and optimization to reduce inefficiencies and unlock backhaul opportunities.

Business Impact

+30% efficiency; +5% backhaul

Scale

USA & Mexico operations

Read Full Case Study
AI Market Mix + 5G Targeting (Huawei)

AI Market Mix + 5G Targeting (Huawei)

PythonXGBoostGeospatialMarket Mix ModelingOptimization

Telecom commercial and network planning required data-driven models for expansion, pricing, and customer targeting.

Business Impact

$40M; +39% targeting

Scale

Multi-market deployment

Read Full Case Study
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Research Papers

Applied AI & Optimization Research

Peer-reviewed work bridging optimization and applied ML systems

Waste Collection of Touristics Services Sector Residues Vehicle Routing Problem with Time Windows to an Industrial Polygon in a Smart City
2021
Lecture Notes in Intelligent Transportation and Infrastructure, Springer

Waste Collection of Touristics Services Sector Residues Vehicle Routing Problem with Time Windows to an Industrial Polygon in a Smart City

Diego Hurtado-Olivares, José Alberto Hernández-Aguilar, Alberto Ochoa-Zezzatti, José Crispín Zavala-Díaz, Guillermo Santamaría-Bonfil

Presents an optimization framework for solid waste collection in smart cities, utilizing a heuristic algorithm that combines greedy initialization with simulated annealing for route improvement.

Smart CitiesVRPTWWaste ManagementMetaheuristics
Humanitarian Logistics for the Optimal and Timely Evacuation in High Buildings Within a Smart City Using an Adaptive Metaheuristic Context
2021
Lecture Notes in Intelligent Transportation and Infrastructure, Springer

Humanitarian Logistics for the Optimal and Timely Evacuation in High Buildings Within a Smart City Using an Adaptive Metaheuristic Context

Peter Savier Oropeza-Martínez, José Alberto Hernández-Aguilar, Alberto Ochoa-Zezzatti, Diego Hurtado-Olivares

Evaluates adaptive metaheuristic models for evacuating high-rise buildings during emergencies, incorporating heterogeneous crowd simulation to study dynamic agent behavior.

Humanitarian LogisticsEvacuationCrowd SimulationMetaheuristics
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Medium Posts

Technical Writing

Articles on applied ML, modeling foundations, and practical data science systems

Predicting Taxi Fare in New York City
Medium
Aug 202412 min read
Feature EngineeringXGBoostGeospatial

Predicting Taxi Fare in New York City

Feature engineering, geospatial signals, and gradient boosting to build a robust pricing model.

Customer Churn Prediction Using Machine Learning
Medium
Mar 202317 min read
ChurnClassificationModeling

Customer Churn Prediction Using Machine Learning

A practical walkthrough of churn modeling and evaluation, including feature engineering and model selection.

Linear Regression from Scratch
Medium
202010 min read
OptimizationPythonMath

Linear Regression from Scratch

Rebuilding core optimization concepts (cost functions and gradient descent) using NumPy to deepen intuition for ML foundations.

Make a Covid-19 Choropleth Map in Mapbox
Medium
Apr 20207 min read
GeospatialMapboxVisualization

Make a Covid-19 Choropleth Map in Mapbox

End-to-end guide to geospatial visualization using Mapbox, data joins, and styling for choropleth maps.

COVID-19 Coronavirus: Top Ten Most Affected Countries
Medium
Jun 20208 min read
Time SeriesAnalyticsCOVID-19

COVID-19 Coronavirus: Top Ten Most Affected Countries

Time-series analysis and normalization techniques to compare outbreak trajectories across countries.

Analyze and Visualize Data for COVID-19: Mexico
Medium
Apr 20206 min read
Data CleaningETLVisualization

Analyze and Visualize Data for COVID-19: Mexico

A regional deep dive into data cleaning, ETL, and visualization for public health datasets.

Covid-19: An Overview of Mexico
Medium
20207 min read
AnalyticsCOVID-19Mexico

Covid-19: An Overview of Mexico

An integrated overview of pandemic metrics and trends for Mexico.

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TESTIMONIALS

What People Say

Feedback from colleagues and leaders I've worked with

"

"I worked side by side with Diego for more than a year. We made amazing things for Huawei, like creating a new methodology (Lifestyle Zones) for 4G sites optimization and 5G deployment - this project generated more than US$40M in revenues. Always in a good mood, always creative and results-oriented, Diego is the best colleague you could have in a Consulting team."

Huawei Technologies

Andres Garcia Jaramillo

Senior Manager, Business Consulting

Huawei Technologies

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"I worked with Diego on Business analytics projects and taken advantage of his excellent analytical and modelling skills. Diego has a great ability to assemble data from multiple sources and apply logic and mathematical tools to help identify value creation opportunities. Diego has a clear and structured approach to his work."

Huawei Technologies

Mohammed Wargui, Ph.D., MBA

Principal Business Consultant

Huawei Technologies

"

"Diego supported and provided data science knowledge to state-of-the-art data-based projects for several Telcos in Latam. With his dedicated and diligent support, we delivered on-time innovative business solutions and methodologies. Apart from his high professionalism and knowledge, he was a truly team worker and helped the team to glue together."

Huawei Technologies

Paola Rozada

Managing Business Consultant

Huawei Technologies

"

"I had the opportunity to work with Diego as part of our Data Science team. He consistently delivered valuable results by aligning technical work with business impact. Diego stood out as a great team player—always willing to support colleagues and help new members onboard. His flexibility and openness to change made him an asset in dynamic environments."

Walmart

Act. Miriam Elizabeth López

Lead Data Scientist

Walmart

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"Diego always performed in a mature professional way: strong technical skills in the creation of analytics algorithms and dashboards; enthusiasm, devotion and energy to execute his projects; good capability for insights discovery based on his analytics; and initiative for self guidance + self management. I fully recommend him for effective team work."

Huawei Technologies

Felipe González Carrasco

Strategy Team

Huawei Technologies

"

"I knew Diego Hurtado during our time together in Huawei - I can confirm his excellent human quality and professionalism when Data Science was involved into the discussions. I can say that he is a very good professional with the highest quality standards."

Huawei Technologies

Raúl Maldonado

Senior Business Architect

Huawei Technologies

"

"I have the pleasure to count Diego as a colleague. He is a star in the rising. His comprehension on everything related to Data Analytics is far beyond his age. Invaluable contributions. Pristine work ethics. A true team player. Most of all, Diego is a fine, fine gentleman."

Huawei Technologies

Jose Miguel Fletcher

Operating Partner and Chairman

Huawei Technologies

"

"Diego Hurtado was my student during his Master's degree in Computer Science at UNAM. He demonstrated great skills in optimization and metaheuristics, as well as a strong ability to apply theoretical concepts to real-world problems. His dedication and passion for learning were evident throughout his studies, making him an outstanding student and researcher."

National Autonomous University of Morelos

Carlos Alberto Hernández Aguilar

SNI 2: Professor Researcher

National Autonomous University of Morelos

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