Alejandro Correa Bahnsen

Alejandro Correa Bahnsen

Bogotá - Bogota, Colombia
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Alejandro Correa Bahnsen

Alejandro Correa Bahnsen

Bogotá - Bogota, Colombia
Member since July 20, 2015
Alejandro holds a PhD in Machine Learning. He has over 8 years of experience developing data science projects in different areas such as credit card fraud detection, credit scoring, collections, churn, and direct marketing. He enjoys giving talks on successful applications of big data science to different organizations. Moreover he is an active contributor to several open source projects such as scikit-learn.
Alejandro is now available for hire
  • R, 9 years
  • Data Science, 9 years
  • Machine Learning (ML), 8 years
  • Python, 6 years
  • Scikit-learn, 6 years
  • Big Data, 5 years
  • NoSQL, 3 years
  • Apache Spark, 3 years
Bogotá - Bogota, Colombia
Preferred Environment
Linux Mint, Python, PyCharm, Jupyter, R, R-Studio
The most amazing...
...thing I've helped develop is CostCla, a Python library for implementation of several cost-sensitive machine learning models to solve real-wold problems.
  • Lead Data Scientist
    CrunchFlow (via Toptal)
    2016 - PRESENT
    • Created human resource analytics models.
    • Forecasted employee churn.
    • Forecasting candidates' KPIs using machine learning.
    • Optimized resource allocation.
    • Created a different kind of API to allow usage of machine learning modules.
    Technologies: Python, Azure, Machine Learning
  • Lead Data Scientist
    Easy Solutions, Inc.
    2015 - PRESENT
    • Managed the data science team.
    • Developed machine learning models for information security.
    Technologies: Python, R, Sklearn, Big Data, NoSQL
  • Professor of the Master in Analytics
    Universidad de los Andes
    2016 - 2016
    • Oversaw courses in natural language processing, big data, and machine learning.
    Technologies: Machine Learning, Statistics, Data Science, Natural Language Processing
  • PhD Researcher
    University of Luxembourg
    2012 - 2015
    • Developed example-dependent cost-sensitive classification techniques.
    • Created a machine learning technique tailor-made for credit card fraud detection.
    • Applied cost-sensitive predictive modeling to a variety of real-world applications such as credit card fraud detection, credit scoring, churn modeling, and direct marketing.
    Technologies: Python, R, Sklearn, Spark, SQL
  • Fraud Data Scientist
    SIX Financial Services
    2012 - 2015
    • Developed intelligent reporting to support the card management team.
    • Implemented advanced cost-sensitive classification credit card fraud detection models.
    Technologies: Python, Sklearn, R, SQL, Oracle
  • Data Scientist
    Scotia Bank/Colpatria Bank
    2010 - 2012
    • Implemented genetic algorithm and particle swarm optimization models in SAS for selecting the best architecture of a multi-layer perceptron neural network, and for selecting the variables that maximize the KS statistic in a logistic regression model.
    • Created different cluster analyses for the risk and marketing areas, for clients segmentation and model segmentation, among others.
    Technologies: SAS, R, VBA, MATLAB, PHP, SQL
  • Statistical Models Analyst
    GE Money/Colpatria Bank
    2008 - 2010
    • Developed acquisition and behavior scorecards for calculating clients' probability of default, using logistic regression, CHAID decision trees for variables binning, binary genetic algorithm optimization for variable selection, and multi-layer perceptron neural networks.
    • Created a constraint optimization algorithm for assigning collection treatments to bank clients, using the probability of a client of falling in next bucket as an input, the expected response per client per treatment, total balance, and treatments costs.
    Technologies: SAS, SPSS, R, SQL, VBA, PHP, MATLAB
  • Six Sigma Intern
    The Dow Chemical Company
    2006 - 2008
    • Developed reports for the commercial and marketing areas.
    • Created GARCH and ARIMAX models for forecasting raw materials prices.
    • Responsible for a Six Sigma project for time cycle reduction on international orders. The result was the building of a new warehouse on a Colombian free trade zone.
    • Developed several marketing research projects for plastics, construction, and chemical departments.
    Technologies: Oracle, VBA, SAS
  • CostCla Python Library (Development)

    CostCla is a Python module for cost-sensitive machine learning (classification) built on top of Scikit-Learn and SciPy and distributed under the 3-Clause BSD license.

    In particular, it provides a set of example-dependent cost-sensitive algorithms and different real-world example-dependent cost-sensitive datasets.

  • Contributor Sklearn (Other amazing things)

    Contributor to the scikit-learn project.

  • Languages
    SQL, SAS, R, Python, Visual Basic for Applications (VBA), C, C++
  • Libraries/APIs
    Scikit-learn, SciPy, NumPy, Flask-RESTful, Node.js
  • Tools
    IPython Notebook, Microsoft Excel, MATLAB
  • Paradigms
    Data Science, REST
  • Misc
    Machine Learning (ML), Data Structures, Algorithms, Natural Language Processing (NLP), Optimization Algorithms, Data Mining, Statistics, Deep Learning, Applied Mathematics, Big Data
  • Frameworks
    Hadoop, Apache Spark, Flask, Django
  • Platforms
    Amazon Web Services (AWS), Oracle, Ubuntu, Azure, Linux Mint
  • Storage
    MongoDB, PostgreSQL, NoSQL, MySQL
  • Ph.D. degree in Machine Learning
    Luxembourg University - Luxembourg
    2012 - 2015
  • Master's degree in Operations Research, Finance, and Statistics
    Universidad de los Andes - Bogota, Colombia
    2008 - 2010
  • Bachelor degree in Industrial Engineering
    Universidad de los Andes - Bogota, Colombia
    2002 - 2008
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