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Jaime Andrés Castañeda

@jacasta2

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I'm a researcher with ~15-year experience working on experimentation and data science projects

Colombia

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What I'm looking for

I am interested in data science and machine learning roles with career development as a technical leader

I am a Computer Science Engineer, Master in Systems Engineering and PhD in Economics. I have extensive experience leading and working on experimentation and data science projects to strategically support decision-making and drive business results. I have developed experimentation and data science apps, supervised and unsupervised machine learning models using Python, Power BI dashboards and statistical analyses using Stata and SPSS to support decision-making and the development of improved business strategies. I am skilled in Python, SQL, Machine Learning, NLP, Pandas, Numpy, Matplotlib, Seaborn, Scikit-learn, Keras, Streamlit, FastAPI, VS Code, Git, AWS SageMaker, Postgres, Power BI, Stata and SPSS. I am interested in data science and machine learning roles with career development as a technical leader.

Experience

Data Scientist

Colombian ICT Ministry

Mar 2023 - Dec 2023 (9 months)

- Led the construction of a composite index in Python with more than 40,000 school records to support the Internet connectivity prioritization policy
- Developed Python code to clean and extract text from legal documents through regular expressions and prompt engineering using the OpenAI API’s ChatGPT
- Built 5 Power BI dashboards to track the effectiveness of Internet connectivity policy

Python Power BI Data Governance Data Analytics Data Science Data Visualization

Data Science Fellow

Correlation One

Mar 2022 - Jul 2022 (4 months)

- Performed an extract, transform and load (ETL) process with more than 1.5 million traffic accident records using Python, SQL and Postgres
- Developed an unsupervised machine learning model using Python and SQL that clusters highway corridors for road safety operations, prioritizing corridors that total close to 50% of accidents and more than 40% of fatalities

Python SQL Data Visualization Machine Learning ETL Data Analytics Data Science

Current

Data Scientist

Current

Freelance

Feb 2022 - Present (2 years 3 months)

- Deployed a natural language processing (NLP) app in the cloud using the Scopus Search API, Python, Pinecone and Streamlit that lists the 10 publications most similar to the user's interests
- Built a supervised machine learning model using Python, Hopsworks and Streamlit with NBA data that shows that improvements in key players' performance increase the chances of winning a game by more than 50%

Data Science Data Analytics Machine Learning NLP Python SQL PostgreSQL Streamlit Git ETL Power BI

Associate Data Researcher - Associate Professor

Universidad del Rosario

Sep 2021 - Jan 2022 (4 months)

- Designed and directed the implementation of a decision-making experiment with more than 500 participants to generate strategies to improve organizational service levels.
- Trained supervised machine learning models using Python that show that expedited shipping increases inventory availability by around 20%

Experimental Design Python Machine Learning Data Analytics Data Science Research Supply Chain Management

Assistant Data Researcher - Assistant Professor

Universidad del Rosario

Apr 2016 - Sep 2021 (5 years 5 months)

- Designed and led the implementation of a decision-making experiment to test risk mitigation strategies that scale manufacturing levels
- Built supervised machine learning models using Stata that show how risk-sharing contracts increase inventory availability by around 5%
- Performed data science analyses that show how inventory transshipment increases supply chain efficiency by more than 10%

Research Experimental Design Data Science Data Analytics Machine Learning Stata Supply Chain Management

Data Researcher - Postdoctoral Fellow

Massachusetts Institute of Technology

Feb 2014 - Aug 2015 (1 year 6 months)

- Designed and led the implementation of a decision-making experiment to analyze the strategic allocation of resources to a product portfolio
- Developed predictive models using machine learning techniques that show how excess resources generate inefficiencies of around 15% in their allocation to an inventory portfolio

Data Analytics Stata Experimental Design Research Data Science Machine Learning Supply Chain Management

Data Researcher - Doctoral Assistant

Università della Svizzera italiana

Sep 2009 - Aug 2013 (3 years 11 months)

- Designed and directed the implementation of 3 experiments on supply chain management strategies, evaluating their effectiveness with data science and machine learning techniques
- Conducted more than 10 semi-structured interviews for a humanitarian logistics business case in Côte d'Ivoire, identifying logistics services options that increase the effectiveness of aid delivery by more than 50%