About the team TikTok's Data Cycling Center Team focuses on building content, understanding, and data-driven solutions for both internal stakeholders and tools for external users. We focus on both delivering human understanding and direct content understanding helping solve large impact problems from that understanding. Responsibilities - Advanced Project Management: Direct and coordinate projects, orchestrating efforts across a large, interdisciplinary team of policy, product managers, and data labelers, ensuring timely and efficient execution of tasks. - Clarification and Simplification of Product Requirements: Diligently comprehend product needs, drive clear communication, and decompose technical tasks into more manageable units, ensuring a smooth execution path. - Provide Clear and Strong Data Insights: Responsible for building dashboards and delivering analytical reports to identify improvement opportunities across Policy, Modeling, and Product Management teams. Be the owner of action items to drive concrete impact from analytical results. - Collaborative Experimentation and Documentation: Work in tandem with various teams to formulate meticulous experiment plans, documenting results with utmost precision, and patiently addressing inquiries from both technical and non-technical stakeholders.
Minimum Qualifications -Bachelor's/Master's degree in Computer Science, Computer Engineering, or other relevant majors. -2-3 years of experience working with SQL, Dashboarding, and Analytical Expertise: Demonstrates intermediate-to-advanced proficiency in SQL and dashboard building, ensuring structured, efficient, and scalable data management, and leveraging data to inform strategic decision-making. -2-3 years of experience working with Python: Possesses intermediate-to-advanced skills in Python programming, showcasing the ability to develop and implement robust data science solutions. - Statistical Knowledge: Demonstrates strong statistical background and can leverage statistical knowledge in solving business analytical requirements. A deep understanding of concepts includes but is not limited to: Hypothesis Testing, Confidence Interval, Statistical Significance, Margin of Error, A/B testing techniques, and measurement. - Strategic Interpersonal Skills: Displays formidable interpersonal skills, embodying an ability to seize new opportunities, be able to set product directions strategically, ignite innovative ideas, and marshal support to bring products from conceptualization to realization. - Knowledge of Machine Learning: Demonstrated fundamental knowledge of the end-of-end machine learning model development process. Understand how data plays a crucial role in terms of model quality and model iteration. Preferred Qualifications -Creative thinking and a passion for innovation. -Knowledge of the AIGC modeling process: Demonstrate a basic understanding of transformer architecture and MLLM models (T2I and T2V). -Understand the data curation process and model evaluation criteria when developing AIGC models.
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