Alejandro Correa Bahnsen
Verified Expert in Engineering
Data Science Developer
Bogotá - Bogota, Colombia
Toptal 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.
Portfolio
Experience
- Data Science - 9 years
- R - 9 years
- Machine Learning - 8 years
- Python - 6 years
- Scikit-learn - 6 years
- Big Data - 5 years
- Apache Spark - 3 years
- NoSQL - 3 years
Preferred Environment
Python, Solution Architecture, Apache Airflow, Amazon Web Services (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.
Work Experience
Lead Data Scientist
Easy Solutions, Inc.
- Managed the data science team.
- Developed machine learning models for information security.
Chief Artificial Intelligence Officer
Rappi
- 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.
Professor of the Master in Analytics
Universidad de los Andes
- Oversaw courses in natural language processing, big data, and machine learning.
PhD Researcher
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.
Fraud Data Scientist
SIX Financial Services
- Developed intelligent reporting to support the card management team.
- Implemented advanced cost-sensitive classification credit card fraud detection models.
Data Scientist
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.
Statistical Models Analyst
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.
Six Sigma Intern
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.
Experience
Tutorial EDCS Credit Scoring
CostCla Python Library
https://github.com/albahnsen/CostSensitiveClassificationIn particular, it provides a set of example-dependent cost-sensitive algorithms and different real-world example-dependent cost-sensitive datasets.
Contributor Sklearn
Education
Ph.D. Degree in Machine Learning
Luxembourg University - Luxembourg
Master's Degree in Operations Research, Finance, and Statistics
Universidad de los Andes - Bogota, Colombia
Bachelor Degree in Industrial Engineering
Universidad de los Andes - Bogota, Colombia
Skills
Libraries/APIs
Scikit-learn, NumPy, SciPy, Flask-RESTful, Node.js, Pandas
Tools
IPython Notebook, Microsoft Excel, MATLAB, PyCharm, Jupyter, SPSS, Apache Airflow, IPython
Languages
SAS, Python, SQL, R, Visual Basic for Applications (VBA), PHP, C++, C, Snowflake
Platforms
Azure, Amazon Web Services (AWS), Oracle, Ubuntu, RStudio, Linux Mint, Google Cloud Platform (GCP), Jupyter Notebook
Frameworks
Flask, Hadoop, Apache Spark, Spark, Django
Storage
MongoDB, PostgreSQL, NoSQL, MySQL, Data Lakes
Paradigms
REST, Management
Other
Data Structures, Algorithms, Big Data, Applied Mathematics, Machine Learning, Natural Language Processing (NLP), Data Science, Deep Learning, Statistics, Data Mining, Optimization Algorithms, Data Analysis, Generative Pre-trained Transformers (GPT), Solution Architecture, Chatbots, Recommendation Systems, APIs
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