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Carlos del Cacho, Artificial Intelligence (AI) Developer in Madrid, Spain
Carlos del Cacho

Artificial Intelligence (AI) Developer in Madrid, Spain

Member since November 2, 2019
With 15+ years of experience, Carlos has deep technical knowledge within the AI space. A rare breed with expertise in data engineering, data science, and general software architecture. A techie with a business heart, he has gained wisdom in online business models, retention strategies, churn analysis, LTV computation, and sales forecasting within a variety of industries.
Carlos is now available for hire
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Portfolio

Experience

Location

Madrid, Spain

Availability

Part-time

Preferred Environment

Amazon Web Services (AWS), Elasticsearch, Apache Lucene, Apache Spark, Scikit-learn, Java, R, Python

The most amazing...

...accomplishment thus far in life is keeping the curiosity of a toddler to continue learning after all these years.

Employment

  • Solutions Architect

    2020 - PRESENT
    Databricks
    • Designed solutions for customers on top of the Databricks platform.
    • Provided technical support to the sales team, delivered presentations and workshops to customers to close business.
    • Assisted with deployments of the platform in a multi-cloud environment (AWS/Azure).
    Technologies: Amazon Web Services (AWS), Spark

  • Big Data and AI Tech Lead

    2019 - 2020
    Paradigma Digital
    • Consulted across several industries, including banking (consumer finance), media, and utilities.
    • Provided project management within the data science space, leading teams of up to five individual contributors.
    • Hired and screened technical staff, including data scientists, data engineers, big data architects, and data governance consultants.
    Technologies: Amazon Web Services (AWS), Scikit-learn, Python

  • Data Science Manager

    2016 - 2019
    Stratio Big Data
    • Segmented products in sales levels using unsupervised machine learning for personalized treatment when building predictive models.
    • Overhauled the architecture to improve the scalability of the system. Performing 20 million daily regressions within a demand forecasting problem in a distributed cluster in less than 8 hours.
    • Led a data science team of five engineers within a demand forecasting project in retail.
    • Developed new business development and analytics (presales). Held a 30% conversion rate from proposal to contract in data science projects over my tenure in presales.
    • Assisted deals in retail, media, education, banking, marketing, and utility industry sectors.
    Technologies: Scikit-learn, Python, Hue, Impala, Apache Hive, Kudu, HDFS, Spark, Cloudera

  • Chief Data Scientist

    2014 - 2016
    Jobandtalent
    • Designed and implemented a matching algorithm for job offer recommendations based on conditional relevance models by analyzing career paths in resume databases.
    • Doubled the conversion rate of the recommender pipeline with the algorithm, resulting in an equivalent increase in the number of monthly job applications.
    • Prototyped a system for improving customer segmentation in email marketing in order to increase sales of online courses, with the idea of targeting users at the micro-level as opposed to targeting them by area of expertise.
    • Created a distributed system on top of Elastic MapReduce for tuning machine learning hyperparameters, accelerating run time of grid searches by 50x in an information retrieval application.
    • Proactively wrote a tool to automate dashboard generation and trained the BI team on its usage, shaving weekly hours of routine work from their schedule.
    • Delivered lectures to co-workers on Information Retrieval concepts.
    • Authored feature description specifications for several modules, defining the long term vision of the recommendation algorithm.
    • Screened machine learning engineers in hiring processes conducting knowledge assessments within area of expertise.
    Technologies: Discriminant Analysis (LDA), Topic Modeling, Amazon S3 (AWS S3), Redshift, Cloud Storage, BigQuery, R, PHP, Java, Redis, Apache Lucene, Hadoop

Experience

  • Sentiment Analysis for Political Forecasting

    Crawling of social media (Twitter) and filtering based on specific keywords to retrieve and classify sentiment with regards to the Peace Plebiscite that took place in Colombia in October 2016. Classification through recurrent neural networks with deeplearning4j.

  • Recommender System for Olympic Channel
    https://www.olympicchannel.com

    Developed a personalization module based on ElasticSearch and text classification through linear kernel SVMs that attained 93% accuracy in tagging video metadata content automatically. Lead the development team and managed customer engagement. The system is designed over cloud technology in AWS to withstand peak traffic loads of over 150 million page views per month for the Tokyo 2020 games.

  • Credit Risk Scoring for a Financial Institution
    https://www.bancosantander.es

    Developed a hierarchical logistic model tree for assessing loan risk that departed from the bank's methodology and incorporated non-traditional signals from public datasets such as events in the Companies House Records (changes in management, refinancing, bankruptcies, etc).

  • Demand Forecasting for an F500 Retailer

    Created a distributed system to predict daily unit product sales in over a thousand stores across Spain, performing 20 million regressions on a daily basis, improving accuracy, and delivering cost efficiencies in the supply chain by reducing excess inventory while avoiding stock-outs. Technologies: Apache Spark, Python, and scikit-learn.

  • Inventory Storage for an Order Management System

    Developed an internal software with custom ranking functions over Apache Solr to dynamically check for article inventory in over a thousand stores with response times in milliseconds, prioritizing available locations by distance in search engine results.

Skills

  • Languages

    R, Python, SQL, Java, PHP, C++, JavaScript

  • Frameworks

    Hadoop, Apache Spark, Spark, LightGBM

  • Libraries/APIs

    Apache Lucene, SpaCy, PySpark, Scikit-learn, NumPy, SciPy, XGBoost, CatBoost

  • Other

    Machine Learning, Algorithms, Artificial Intelligence (AI), Web Scraping, Text Mining, Recommendation Systems, Presales, Statistics, Big Data, Scalability, Predictive Analytics, Association Rule Learning, Information Retrieval, Gradient Boosted Trees, Topic Modeling, Natural Language Processing (NLP), Neural Networks, Linear Regression, Economics, Financial Markets, Hue, Cloud Storage, Email Marketing, Online Marketing, Business Strategy, Data Mining, Churn Analysis, Acquisition Analysis, Marketing Attribution, Bayesian Statistics, Genetic Algorithms, A/B Testing, Deep Learning, Google Ads, Support Vector Machines (SVM), Discriminant Analysis (LDA), Logistic Regression, Random Forests, Naive Bayes, Text Classification, Sentiment Analysis, Kubernetes Operations (Kops), Model Validation, Lambda Functions

  • Tools

    Solr, Cloudera, Impala, BigQuery, Weka, Google Analytics, Git, Kudu

  • Paradigms

    Scrum, Conversion Rate Optimization (CRO), Linear Programming, Business Intelligence (BI), MapReduce, Anomaly Detection, Data Science, ETL

  • Storage

    Elasticsearch, PostgreSQL, MySQL, MongoDB, Apache Hive, Redis, HDFS, NoSQL, Data Validation, Redshift, Amazon S3 (AWS S3)

  • Platforms

    Amazon Web Services (AWS), RapidMiner, AWS Lambda, Amazon EC2, Kubernetes, H2O Deep Learning Platform, Docker

  • Industry Expertise

    Retail & Wholesale

Education

  • Master's Degree in Artificial Intelligence
    2013 - 2015
    Universidad Autónoma de Madrid - Madrid, Spain
  • Progress towards a Bachelor of Arts Degree in Economics
    2009 - 2010
    UNED - Madrid, Spain
  • Master's Degree in Computer Science
    1999 - 2003
    Universidad Autónoma de Madrid - Madrid, Spain

Certifications

  • AWS Solutions Architect Associate
    JANUARY 2021 - JANUARY 2024
    Amazon Web Services
  • Google Cloud Platform Fundamentals: Core Infrastructure
    AUGUST 2019 - PRESENT
    Google via Coursera
  • Essential Cloud Infrastructure: Foundation
    AUGUST 2019 - PRESENT
    Google via Coursera
  • Convolutional Neural Networks
    JUNE 2018 - PRESENT
    deeplearning.ai via Coursera
  • Structuring Machine Learning Projects
    MAY 2018 - PRESENT
    deeplearning.ai via Coursera
  • Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
    APRIL 2018 - PRESENT
    deeplearning.ai via Coursera
  • Neural Networks and Deep Learning
    MARCH 2018 - PRESENT
    deeplearning.ai via Coursera
  • Excel Skills for Business: Advanced
    MARCH 2018 - PRESENT
    Macquarie University via Coursera
  • Excel Skills for Business: Intermediate II
    FEBRUARY 2018 - PRESENT
    Macquarie University via Coursera
  • Excel Skills for Business: Intermediate I
    FEBRUARY 2018 - PRESENT
    Macquarie University via Coursera
  • Excel Skills for Business: Essentials
    FEBRUARY 2018 - PRESENT
    Macquarie University via Coursera
  • Cost and Economics in Pricing Strategy
    NOVEMBER 2017 - PRESENT
    University of Virgina via Coursera
  • Trading Algorithms
    JUNE 2017 - PRESENT
    Indian School of Business via Coursera
  • Google Analytics Certification
    JULY 2016 - PRESENT
    Google
  • Google Adwords Certification
    JULY 2016 - PRESENT
    Google
  • Foundations of Business Strategy
    MAY 2016 - PRESENT
    University of Virginia via Coursera
  • Entrepreneurship 1: Developing the Opportunity
    MAY 2016 - PRESENT
    University of Pennsylvania via Coursera
  • Advanced Business Strategy
    MAY 2016 - PRESENT
    University of Virginia via Coursera
  • Operations Analytics
    APRIL 2016 - PRESENT
    University of Pennsylvania via Coursera
  • Customer Analytics
    JANUARY 2016 - PRESENT
    University of Pennsylvania via Coursera
  • Data Visualization
    AUGUST 2015 - PRESENT
    University of Illinois via Coursera
  • Text Mining and Analytics
    JULY 2015 - PRESENT
    University of Illinois via Coursera
  • Introduction to Big Data with Apache Spark
    JULY 2015 - PRESENT
    Databricks via EdX
  • Cluster Analysis in Data Mining
    JUNE 2015 - PRESENT
    University of Illinois via Coursera
  • Text Retrieval and Search Engines
    APRIL 2015 - PRESENT
    University of Illinois via Coursera
  • Pattern Discovery in Data Mining
    MARCH 2015 - PRESENT
    University of Illinois via Coursera
  • Data Analysis and Statistical Inference
    NOVEMBER 2014 - PRESENT
    Duke University via Coursera
  • Model Thinking
    JUNE 2014 - PRESENT
    University of Michigan via Coursera
  • Cloudera Certified Developer for Apache Hadoop
    APRIL 2013 - PRESENT
    Cloudera
  • Computing for Data Analysis
    FEBRUARY 2013 - PRESENT
    Johns Hopkins University via Coursera
  • Networked Life (Social Network Analysis)
    OCTOBER 2012 - PRESENT
    University of Pennsylvania via Coursera
  • Game Theory
    MAY 2012 - PRESENT
    Stanford University via Coursera

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