Global Data Science Intern
hace 1 día
Semester(s): 5th – 10th semester
Degree(s): ITC, Mathematics, Data Science, Actuarial Science, Industrial Physics, Mechatronics
Tentative Start Date (month): November 2025
Project Objective
Support the Global Data Science team in the phases of problem exploration and definition of descriptive, predictive, and prescriptive models, as well as in visualization tools and model consumption. Also, provide support in data and model validati
Challenges for the Student- Understand business needs
- Generate value through exploratory data analysis
- Work in a team and be results-oriented
- Use the technology stack used at CEMEX for data science (Jira, Python, SQL, Databricks, Snowflake)
- Identify and map data sources and develop queries
- Process data and conduct exploratory data analysis using visualization dashboards
- Formulate hypotheses, design experiments, and develop statistical validation tests
- Perform feature engineering
- Develop prediction or prescription models using Machine Learning or other Artificial Intelligence techniques
- Validate and improve models
- Programming in scripting languages such as R or Python (preferably Python)
- Familiarity with visualization dashboards such as Tableau or PowerBI
- Desirable knowledge of CSS, HTML, Snowflake
- Teamwork
- Storytelling with data (visualizations, statistical hypothesis testing)
- Problem-solving orientation
Semester(s): 5th – 10th semester
Degree(s): ITC, Mathematics, Data Science, Actuarial Science, Industrial Physics, Mechatronics
Tentative Start Date (month): November 2025
Project Objective
Support the Global Data Science team in the phases of problem exploration and definition of descriptive, predictive, and prescriptive models, as well as in visualization tools and model consumption. Also, provide support in data and model validati
Challenges for the Student- Understand business needs
- Generate value through exploratory data analysis
- Work in a team and be results-oriented
- Use the technology stack used at CEMEX for data science (Jira, Python, SQL, Databricks, Snowflake)
- Identify and map data sources and develop queries
- Process data and conduct exploratory data analysis using visualization dashboards
- Formulate hypotheses, design experiments, and develop statistical validation tests
- Perform feature engineering
- Develop prediction or prescription models using Machine Learning or other Artificial Intelligence techniques
- Validate and improve models
- Programming in scripting languages such as R or Python (preferably Python)
- Familiarity with visualization dashboards such as Tableau or PowerBI
- Desirable knowledge of CSS, HTML, Snowflake
- Teamwork
- Storytelling with data (visualizations, statistical hypothesis testing)
- Problem-solving orientation
Semester(s): 5th – 10th semester
Degree(s): ITC, Mathematics, Data Science, Actuarial Science, Industrial Physics, Mechatronics
Tentative Start Date (month): November 2025
Project Objective
Support the Global Data Science team in the phases of problem exploration and definition of descriptive, predictive, and prescriptive models, as well as in visualization tools and model consumption. Also, provide support in data and model validati
Challenges for the Student- Understand business needs
- Generate value through exploratory data analysis
- Work in a team and be results-oriented
- Use the technology stack used at CEMEX for data science (Jira, Python, SQL, Databricks, Snowflake)
- Identify and map data sources and develop queries
- Process data and conduct exploratory data analysis using visualization dashboards
- Formulate hypotheses, design experiments, and develop statistical validation tests
- Perform feature engineering
- Develop prediction or prescription models using Machine Learning or other Artificial Intelligence techniques
- Validate and improve models
- Programming in scripting languages such as R or Python (preferably Python)
- Familiarity with visualization dashboards such as Tableau or PowerBI
- Desirable knowledge of CSS, HTML, Snowflake
- Teamwork
- Storytelling with data (visualizations, statistical hypothesis testing)
- Problem-solving orientation
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