Lead Data Scientist
2015 - PRESENTEasy Solutions, Inc.- Managed the data science team.
- Developed machine learning models for information security.
Technologies: NoSQL, Big Data, Scikit-learn, R, PythonChief Artificial Intelligence Officer
2019 - 2022Rappi- Utilized machine learning for forecasting candidates' KPIs.
- Optimized resource allocation and created recommendation engines.
- Created a different API type to allow the use of machine learning modules.
Technologies: Machine Learning, Python, AWS, Management, Fast ApiProfessor of the Master in Analytics
2016 - 2016Universidad de los Andes- Oversaw courses in natural language processing, big data, and machine learning.
Technologies: Natural Language Processing (NLP), Data Science, Statistics, Machine LearningPhD Researcher
2012 - 2015University 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: SQL, Spark, Scikit-learn, R, PythonFraud Data Scientist
2012 - 2015SIX Financial Services- Developed intelligent reporting to support the card management team.
- Implemented advanced cost-sensitive classification credit card fraud detection models.
Technologies: Oracle, SQL, R, Scikit-learn, PythonData Scientist
2010 - 2012Scotia 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: SQL, PHP, MATLAB, Visual Basic for Applications (VBA), R, SASStatistical Models Analyst
2008 - 2010GE 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: MATLAB, PHP, Visual Basic for Applications (VBA), SQL, R, SPSS, SASSix Sigma Intern
2006 - 2008The 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: SAS, Visual Basic for Applications (VBA), Oracle
Alejandro Correa Bahnsen
Machine Learning Developer in Bogotá - Bogota, Colombia
Member since October 9, 2015
Alejandro holds a PhD in machine learning. He has over 15 years of experience developing data science projects in different areas, including credit card fraud detection, credit scoring, collections, churn, and direct marketing. While working at Rappi, Latam's largest tech unicorn, Alejandro led a team of more than 100 data scientists. He actively contributes to open-source projects such as scikit-learn.
Alejandro is now available for hire
Portfolio
- Easy Solutions, Inc.NoSQL, Big Data, Scikit-learn, R, Python
- RappiMachine Learning, Python, AWS, Management, Fast Api
- Universidad de los AndesNatural Language Processing (NLP), Data Science, Statistics, Machine Learning
Experience
- R 9 years
- Data Science 9 years
- Machine Learning 8 years
- Python 6 years
- Scikit-learn 6 years
- Big Data 5 years
- Apache Spark 3 years
- NoSQL 3 years
Availability
Full-time
Preferred Environment
Python, Solution Architecture, Apache Airflow, AWS, Google Cloud Platform (GCP), Deep Learning, Chatbots, Recommendation Systems, Data Lakes, Snowflake
The most amazing...
...thing I've helped develop is CostCla, a Python library used for implementing several cost-sensitive machine learning models to solve real-world problems.
Employment
Experience
- CostCla Python Libraryhttps://github.com/albahnsen/CostSensitiveClassification
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 Sklearnhttp://scikit-learn.org/
Contributor to the scikit-learn project.
Skills
Languages
SAS, Python, SQL, R, Visual Basic for Applications (VBA), PHP, C++, C, SnowflakeLibraries/APIs
Scikit-learn, NumPy, SciPy, Flask-RESTful, Node.jsTools
IPython Notebook, Microsoft Excel, MATLAB, PyCharm, Jupyter, SPSS, Apache AirflowParadigms
Data Science, REST, ManagementPlatforms
Azure, Amazon Web Services (AWS), Oracle, Ubuntu, RStudio, Linux Mint, Google Cloud Platform (GCP)Other
Data Structures, Algorithms, Big Data, Applied Mathematics, Machine Learning, Natural Language Processing (NLP), Deep Learning, Statistics, Data Mining, Optimization Algorithms, Data Analysis, Solution Architecture, AWS, Chatbots, Recommendation Systems, Fast ApiFrameworks
Flask, Hadoop, Apache Spark, Spark, DjangoStorage
MongoDB, PostgreSQL, NoSQL, MySQL, Data Lakes
Education
- Ph.D. Degree in Machine Learning2012 - 2015Luxembourg University - Luxembourg
- Master's Degree in Operations Research, Finance, and Statistics2008 - 2010Universidad de los Andes - Bogota, Colombia
- Bachelor Degree in Industrial Engineering2002 - 2008Universidad de los Andes - Bogota, Colombia
