Tiktok - Mountain View, CA

posted 3 days ago

Full-time - Mid Level
Mountain View, CA
Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services

About the position

TikTok is the leading destination for short-form mobile video, with a mission to inspire creativity and bring joy. As TikTok continues to grow rapidly on a global scale, we are focused on developing an industry-leading ads measurement product. The Lift Measurement team is dedicated to helping marketers understand the true business value generated by TikTok across all their paid channels. To achieve this, we are building a suite of incrementality measurement products that will provide advertisers with insights into their performance on the TikTok platform. We are seeking an experienced data scientist to join our team, focusing on the development of digital ad measurement products. This role will involve applying experimental design and causal inference methodologies to help advertisers accurately measure their business value derived from TikTok ads. The successful candidate will be responsible for designing and analyzing lift experiments, conducting research to enhance our experimentation platform, and identifying opportunities for new or improved ad measurement products. In this position, you will collaborate with cross-functional teams, including engineers, product managers, and product marketing, to drive product improvements and influence product roadmaps. Your expertise in statistical methodologies and data analysis will be crucial in developing and validating innovative solutions to measurement challenges. We are looking for someone who can work independently in a fast-paced environment and has a strong analytical mindset, along with a passion for digital advertising measurement.

Responsibilities

  • Design and analyze lift experiments to drive product improvements with cross-functional teams
  • Conduct research and analysis to improve the lift experimentation platform using experimental design and causal inference methods
  • Identify opportunities to build new or enhance ad measurement products
  • Develop and validate new approaches to address measurement challenges based on statistically rigorous solutions
  • Build cross-functional relationships with engineers, product managers, product marketing and other key stakeholders to identify opportunities to improve products, drive product launches and influence product roadmaps

Requirements

  • 3+ years industry experience and advanced degree in quantitative discipline (e.g., Statistics, BioStatistics, Political Science, Economics, Quantitative Social Sciences, Computer Science, Mathematics, Physics) or equivalent practical experience
  • Extensive knowledge and experience in statistical methodologies, especially hypothesis testing, experimental design and causal inference
  • Proven experience in querying and analyzing large datasets using SQL/Hive, and proficient in scripting languages like Python/R
  • Strong analytical and strategic thinking with demonstrated product sense and leadership in working environment
  • Able to work independently in an innovative and fast-paced environment

Nice-to-haves

  • Knowledge or experience in digital advertising measurement (Brand or DR) is a plus
  • Knowledge or experience with privacy technologies is a plus (e.g., secure multi-party computation techniques, differential privacy, federated learning)

Benefits

  • 100% premium coverage for employee medical insurance
  • Approximately 75% premium coverage for dependents
  • Health Savings Account (HSA) with a company match
  • Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life and AD&D insurance plans
  • Flexible Spending Account (FSA) Options like Health Care, Limited Purpose and Dependent Care
  • 10 paid holidays per year
  • 17 days of Paid Personal Time Off (PPTO)
  • 10 paid sick days per year
  • 12 weeks of paid Parental leave
  • 8 weeks of paid Supplemental Disability
  • Mental and emotional health benefits through EAP and Lyra
  • 401K company match
  • Gym and cellphone service reimbursements
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