Senior Data Scientist (Multiple Positions)

Responsibilities

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 platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible.
Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day.
To us, every challenge, no matter how difficult, 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 communities we serve.
Join us.

About the Team
Our team plays a crucial role in ensuring the company’s success. We seek people who are willing to learn and put in the effort to solve problems. Our challenges are not your regular day-to-day problems - you’ll be part of a team that’s developing new solutions to new challenges. It’s working fast, at scale, and we’re making a difference. We are looking for talents to join us on this exciting journey!

Responsibilities
Develop marketing experiments and models and run scenario analysis to understand the implications of a variety of business decisions on key metrics and share the insights with marketing immediate team to influence strategic decisions.
Develop analytic framework in partnership with internal teams to quantify business impact, diagnose issues, and to bring insights using internal and external data.
Define core metrics, build essential data tracking dashboard, and identify opportunities from our database and 3rd party datasets, and convert the insights into real changes.
Influence stakeholders through data-based recommendations and mobilize cross-functional teams by telling compelling stories with data to drive business impact and innovative breakthrough.
Conduct experimentations to analyze user behavior and optimize for the best outcome regarding core metrics.
Improve data foundations and excel in product logic thinking using data-driven analysis and brings distinctive problem-solving skills and impeccable business judgment.
Define KPIs and develop analytic framework to evaluate the impact of marketing investments on user and non-user outcomes via A/B testing and statistical models.
Apply quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products.
Apply quantitative analysis to understand data, provide actionable insights, and measure the data through experimentation and causal inference.
Partner with Marketing, Product, Data Engineering, Finance, User Research, and other teams to solve problems and identify trends and opportunities.
Work with large, complex data sets to solve difficult, non-routine analysis problems by applying advanced analytical methods as needed.
Interact cross-functionally, making business recommendations (e.g., cost-benefit, forecasting, experiment analysis) with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information.

Qualifications

Qualifications
Must have a Master’s degree in Computer Science, Engineering (any), Information Technology, Information Systems Management, Data Science, Data Analytics, Machine Learning, Statistics, Mathematics, Finance, or a related quantitative field, and 3 years of related work experience; OR a Bachelor’s degree in Computer Science, Engineering (any), Information
Technology, Information Systems Management, Data Science, Data Analytics, Machine Learning, Statistics, Mathematics, Finance, or a related quantitative field, and 6 years of related work experience, out of which 5 years must be post-bachelor’s, progressive related work experience.

Of the required experience, must have 3 years of experience in each of the following:
Leveraging advanced data gathering, processing, and analysis techniques to develop and deliver data-driven recommendations to support and influence business decisions;
Designing A/B tests, conducting statistical analysis, and interpreting A/B test results to provide insights for product features;
Conducting forecasting and experiment analysis with presentations through visual displays of quantitative information, using visualization tools Tableau and Excel;
Conducting exploratory and predictive analysis using Python and R programming languages;
Cleaning and processing data using SQL-based languages with large scale relational databases; and
Experience in applying data science techniques and principles to develop marketing analytics an