Data Science Grad Intern

Data Science Grad Intern

Requirements

• Course or project-based experience using analytical software to manipulate data (SQL, Python).
• Course or project-based work using basic data engineering concepts (ETL, ELT).
• Course or project-based experience in machine learning concepts and applications (supervised and unsupervised Learning, feature engineering, model evaluation)
• Familiarity with Apache Airflow and Google Cloud Platforms (e.g., BigQuery, Cloud Storage) is plus but not required.
• Shown ability to communicate technical concepts to a technical audience.
• Highly engaged, ambitious problem solver who is self-motivated and eager to learn.
• Eager to collaborate, become part of a team, and lean-in on asking questions from leadership.

Responsibilities

• Lead a project end-to-end, in close collaboration with a mentor, and understand how the team’s work contributes to the Ad Sales organization overall.
• Collaborate in the maintenance and improvement of our suite of scalable ML tools and data products, including feature stores, model registry, ground truth management, and training and inference pipelines.
• Attend team workshops, prioritization and update meetings to understand ways of working and actively participate and contribute to cross-functional initiatives.
• Perform ad-hoc analysis to support various projects across our Data & Measurement Science team.
• Collaborate with full-time analysts to gain perspective on different aspects of day-to-day projects and responsibilities.
• Network with individuals across the Data & Measurement Science organization, as well as the broader Sales teams, to explore areas of opportunity for Data Science in Advertising.

Preferred Qualifications

• Familiarity with Apache Airflow and Google Cloud Platforms (e.g., BigQuery, Cloud Storage) is plus but not required.

Benefits

No information provided on Benefits.