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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, 8 years
  • Scikit-learn, 6 years
  • Python, 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
    2016 - PRESENT
    CrunchFlow (via Toptal)
    • 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
    2015 - PRESENT
    Easy Solutions, Inc.
    • 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
    2016 - 2016
    Universidad de los Andes
    • Oversaw courses in natural language processing, big data, and machine learning.
    Technologies: Machine Learning, Statistics, Data Science, Natural Language Processing
  • PhD Researcher
    2012 - 2015
    University of Luxembourg
    • 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
    2012 - 2015
    SIX Financial Services
    • 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
    2010 - 2012
    Scotia Bank/Colpatria Bank
    • 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
    2008 - 2010
    GE Money/Colpatria Bank
    • 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
    2006 - 2008
    The Dow Chemical Company
    • 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
    Python, SAS, R, SQL, Visual Basic for Applications (VBA), C, C++
  • Frameworks
    Machine Learning, Hadoop, Apache Spark, Flask, Django
  • Libraries/APIs
    NumPy, SciPy, Scikit-learn, Flask-RESTful, Node.js
  • Tools
    IPython Notebook, Microsoft Excel, MATLAB
  • Paradigms
    Data Science, REST
  • Other
    Optimization Algorithms, Data Structures, Data Mining, Statistics, Natural Language Processing (NLP), Deep Learning, Big Data, Applied Mathematics, Algorithms
  • Platforms
    Ubuntu, Amazon Web Services (AWS), Oracle, Linux Mint, Azure
  • Storage
    PostgreSQL, MongoDB, MySQL, NoSQL
  • Ph.D. degree in Machine Learning
    2012 - 2015
    Luxembourg University - Luxembourg
  • Master's degree in Operations Research, Finance, and Statistics
    2008 - 2010
    Universidad de los Andes - Bogota, Colombia
  • Bachelor degree in Industrial Engineering
    2002 - 2008
    Universidad de los Andes - Bogota, Colombia
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