Data and Machine Learning Intern

This is a fully remote position, open to applicants in Colombia.

📋 Description

• Assist in the design, development, and maintenance of data pipelines to guarantee clean, dependable, and timely data.

• Collaborate with the team to implement and enhance ETL processes.

• Integrate data from diverse sources into warehouses, data lakes, and lakehouses.

• Support data management activities, including data cleaning, validation, and transformation.

• Comprehend business objectives and create models that facilitate their achievement, along with metrics to monitor progress.

• Implement machine learning systems utilizing classical ML, deep learning, and foundation models in accordance with best practices.

• Engage in client communications by assisting in requirement gathering and delivering updates on deliverables.

• Explore and visualize data with a vigilant focus on issues that necessitate data cleaning, as well as variations in data distribution that may impact performance post-deployment.

• Identify and assess model errors.

⛳️ Requirements

• Final year of a bachelor’s degree in Computer Science or a related field.

• Proficient in English.

• Fundamental knowledge of Python, machine learning, and data libraries.

• Basic understanding of databases.

• Knowledge of statistical, machine learning, and deep learning algorithms.

• Experience in visualizing and manipulating large datasets.

• Strong problem-solving skills.

• Bonus: Familiarity with AWS, (Py)Spark, Airflow, Data Lakes, and Data Warehouses.

• Curiosity: Eager to learn and expand in various industries using a modern tech stack.

• Autonomy and positivity: We operate as a fully remote, globally distributed team.

• Teamwork: Enjoy a collaborative working environment.

• Adaptability: Work with a startup mindset and maintain a fast-paced work style.

• Dependable: Capable of delivering high-quality work consistently.

• Please submit your CV in English.

🏝️ Benefits

• Every other Friday off.

• Health bonus.

• Remote and flexible work environment.

• Paid sick days and local holidays.