About this role
Full Time Data Scientist, Risk Data Mining - USDS in healthcare at TikTok in San Jose, California, United States. Apply directly through the link below.
At a glance
- Work mode
- Office
- Employment
- Full Time
- Location
- San Jose, California, United States
Core stack
- Machine Learning
- Cross-functional
- Data Science
- Security
- SOLID
- API
Quick answers
What skills are required?
Machine Learning, Cross-functional, Data Science, Security, SOLID, API.
TikTok is hiring for this role. Visit career page
San Jose, United States
The USDS-Platform and Community Integrity (PaCI) team is missioned to: - Protect U.S. TikTok users, including and beyond content consumers, creators, advertisers;
- Secure platform health and community experience authenticity;
- Build infrastructures, platforms and technologies, as well as to collaborate with many cross-functional teams and stakeholders.
The PaCI team works to minimize the damage of inauthentic behaviors on TikTok platforms, covering multiple classical and novel community and business risk areas such as account integrity, engagement authenticity, anti-spam, API abuse, growth fraud, live streaming security and financial safety, etc. In this team, you'll have a unique opportunity to have first-hand exposure to the strategy of the company in key security initiatives, especially in building scalable and robust, intelligent and privacy-safe, secure, and product-friendly systems and solutions. Our challenges are not some regular day-to-day technical puzzles -- You'll be part of a team that's developing novel solutions to first-seen challenges of a non-stop evolution of a phenomenal product eco-system. The work needs to be fast, transferrable, while still down to the ground to make quick and solid differences.
Responsibilities:
- Build rules, algorithms and machine learning models, to respond to and mitigate business risks in TikTok products/platforms. Such risks include and are not limited to abusive accounts, fake engagements, spammy redirection, scraping, fraud, etc.
- Analyze business and security data, uncover evolving attack motion, identify weaknesses and opportunities in risk defense solutions, explore new space from the discoveries.
- Define risk control measurements. Quantify, generalize and monitor risk related business and operational metrics. Align risk teams and their stakeholders on risk control numeric goals, promote impact-oriented, data-driven data science practices for risks.
- Secure platform health and community experience authenticity;
- Build infrastructures, platforms and technologies, as well as to collaborate with many cross-functional teams and stakeholders.
The PaCI team works to minimize the damage of inauthentic behaviors on TikTok platforms, covering multiple classical and novel community and business risk areas such as account integrity, engagement authenticity, anti-spam, API abuse, growth fraud, live streaming security and financial safety, etc. In this team, you'll have a unique opportunity to have first-hand exposure to the strategy of the company in key security initiatives, especially in building scalable and robust, intelligent and privacy-safe, secure, and product-friendly systems and solutions. Our challenges are not some regular day-to-day technical puzzles -- You'll be part of a team that's developing novel solutions to first-seen challenges of a non-stop evolution of a phenomenal product eco-system. The work needs to be fast, transferrable, while still down to the ground to make quick and solid differences.
Responsibilities:
- Build rules, algorithms and machine learning models, to respond to and mitigate business risks in TikTok products/platforms. Such risks include and are not limited to abusive accounts, fake engagements, spammy redirection, scraping, fraud, etc.
- Analyze business and security data, uncover evolving attack motion, identify weaknesses and opportunities in risk defense solutions, explore new space from the discoveries.
- Define risk control measurements. Quantify, generalize and monitor risk related business and operational metrics. Align risk teams and their stakeholders on risk control numeric goals, promote impact-oriented, data-driven data science practices for risks.