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IEBT Innovation

Data Science Trainee

IEBT Innovation

Trainee in Data Science to develop skills in data analysis and Machine Learning. Opportunity to learn from experienced professionals building data-driven solutions.

Posted 7/25/2026full-timeRemote • 🇧🇷 BrazilEntry LevelWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates strong capabilities in data collection, cleaning, and analysis, with proficiency in Python and SQL for data manipulation. Familiarity with Machine Learning concepts and data visualization tools enhances the ability to support decision-making through statistical analyses and reporting.

Highest-signal resume keywords
Python ProgrammingSQL QueryingMachine LearningStatistical AnalysisData Visualization

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
Data CleaningData AnalysisStatistical MethodsPandasNumPyScikit-LearnR ProgrammingRegression AnalysisHypothesis TestingData Manipulation
Tools & Technologies
Power BITableauLooker
Industry Keywords
Data ScienceInformation SystemsComputer ScienceEngineeringMathematicsStatistics

Tech Stack

Tools & technologies
NumpyPandasPythonScikit-LearnSQLTableau

About the role

Key responsibilities & impact
  • Support the collection, organization, cleaning, and analysis of structured and unstructured data.
  • Assist in the development and validation of Machine Learning models under the guidance of the team.
  • Contribute to statistical analyses to support studies and decision-making.
  • Develop reports and dashboards to present metrics and results.
  • Collaborate with data and technology teams in preparing and processing datasets.
  • Document analyses, processes, and project results.

Requirements

What you’ll need
  • Bachelor's degree in progress or completed within the last 2 years in Computer Science, Engineering, Statistics, Mathematics, Information Systems, Data Science, or related fields.
  • Knowledge of Python (Pandas, NumPy, Scikit-Learn) or R.
  • Basic SQL skills for querying and manipulating data.
  • Basic knowledge of statistics (probability, regression, hypothesis testing).
  • Interest in Machine Learning and Artificial Intelligence.
  • Familiarity with data visualization tools such as Power BI, Tableau, or Looker is a plus.
  • Having completed academic, personal, or research projects related to data will be considered an advantage.

Benefits

Comp & perks
  • Health and dental insurance
  • Remote work allowance
  • Paid leave
  • Birthday day off
  • Health and wellness program
  • Individual Development Program (IDP)