Multimedia Data Scientist Intern: Personalization & Metrics

TikTok; San Jose (CA); Sur place; USD 51 000 - 73 000; Plein temps

Avantages offerts par ce poste

Health insurance

Life insurance

Wellbeing benefits

Paid holidays

Housing allowance

Résumé du poste

TikTok is offering a campus internship in the Multimedia Data Science track. The role emphasizes data-driven optimization of the app experience and collaboration across teams to improve content creation journeys.

The internship provides hands-on exposure, industry insight and growth opportunities in a fast-paced environment. Interns will work on metrics development, experiments, and models to personalize publishing experiences, with rolling applications and clear availability details requested

Qualifications

• Pursuing undergraduate/masters in CS, CE or related field.
• Experience in data science roles, esp. mobile app performance.
• Experience with creation-oriented user behavior.
• Proficient in SQL and Python; familiar with Hive or Spark.

Responsabilités

• Develop the experience metric system and monitoring across content creation stages.
• Conduct experiments and define launch standards for iterations.
• Quantify impact of tool performance on publish rate, retention, engagement.
• Use data mining to understand user needs and build personalized publishing models.
• Collaborate with partners to land solutions for evolving products.
• Advance systemic problem solving and research in cutting-edge methodologies.

Connaissances

Data science experience

Mobile app performance analysis

Experimentation

Communication

Formation

Undergraduate or Master in CS/CE or related technical discipline

Outils

SQL

Python

Hive

Spark

Description du poste

TikTok is offering a campus internship in the Multimedia Data Science track. The role emphasizes data-driven optimization of the app experience and collaboration across teams to improve content creation journeys.

The internship provides hands-on exposure, industry insight and growth opportunities in a fast-paced environment. Interns will work on metrics development, experiments, and models to personalize publishing experiences, with rolling applications and clear availability details requested