About TikTok
TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and its offices include New York, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.
Why Join Us
Creation is the core of TikTok's purpose. Our products are built to help imaginations thrive. This is doubly true of the teams that make our innovations possible. Together, we inspire creativity and enrich life - a mission we aim towards achieving every day. To us, every challenge, no matter how ambiguous, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always. At TikTok, we create together and grow together. That's how we drive impact-for ourselves, our company, and the users we serve. Join us.
Team Introduction
Our mission in the experimentation and evaluation team is to build the next-gen A/B testing platform, that empowers the company to make data-driven decisions for the products. The supported scenarios include recommendations, push, ads, search, mobile app, UI interaction and service upgrades etc.
Our platform's capabilities cover the entire experiment life cycle, from experiment design, experiment creation, metrics calculation, and statistical analysis to final evaluation and launch. In the process of rapid iteration, we provide reliable services for businesses to make bold hypotheses and cautious verification.
Responsibilities
- Analytics: Work independently to define, design, prototype, and implement complex exploratory analysis, w.r.t both theoretical and business perspectives.
- Methodology development: Leverage deep statistical expertise to improve and/or create methodologies
- Teamwork: Participate actively and thoughtfully in multidisciplinary teams to implement algorithms in production
- Communication: Effectively communicate insights and recommendations to support decisions on future research directions
- Mentorship: Oversee the analyses of junior statisticians and data scientists, and support their professional development
Minimum Qualification
- M.S. or Ph.D. in Statistics, Econometrics, Operations Research, Mathematics, Computer Science, or other quantitative fields
- Passion for solving unstructured and non-standard mathematical problems
- Expertise in experimental design and/or Bayesian inference & optimization
- Fluency with SQL or similar
- Proficiency with Python, or other interpreted programming language like R or Matlab
Preferred Qualification
- 2 years experience with Bayesian experiment/optimization system design
- Experience with quasi-experimental causal inference (Rubin causal model/ structural causal model/ instrumental variables etc.)
- In-depth understanding and hands-on experience in wielding tools like graphs.
- 2 years experience with applying modern machine learning techniques and/or collaborating with ML scientists
- Excellent written and oral communication skills, including an ability to translate statistical methods and findings for a non-technical audience
- Comfortable with massive paper searching, reading and composing.
