TikTok Local Services - GNE Lead of Anti-Fraud & Governance Strategies

TikTok Pte. Ltd.
Responsibilities

About the team TikTok Local Services (TikTok GO) is a one-stop commerce solution that connects global users with local services through the creative use of TikTok POI (Points of Interest), short videos, LIVE, and search. It delivers valuable real-life experiences and inspires users to explore the world around them.

With the mission of ""Discover great places, Empower local businesses"" Local Services aims to be the most trusted platform to discover great places and connect local businesses. It helps communities engage with restaurants, hotels, and attractions, equips businesses with new ways to connect with customers and drive transactions, and combines innovative marketing and operational tools to support sustainable growth. At the same time, Local Services creates an inclusive and fair business environment, helping merchants, service providers, creators and other roles to continuously create revenue and improve efficiency.

In this regard, the Governance and Experience team of Local Services seeks to preserve trust and uplift the user experience for TikTok Local Services, by designing and implementing end-to-end programmes that enable a safe, trustworthy and thriving international marketplace. Responsibilities

  • Lead & develop a small team of risks anti-fraud & governance experience experts to drive and create impactful and data-driven policies and strategies.
  • Reduce platform losses and incentive abuses; detect and combat fraudulent online and offline behaviour trying to circumvent enforcement systems -
  • across Merchants, Listings, Content, POIs, Buyers, and Reviewers.
  • Establish policies and processes to collect and manage user feedback; and devise fulfilment and service experience strategies; across Customers, Creators and Sellers.
  • Formulate and implement strategies to ensure a good business experience for Merchants and Creators, while governing fraud and experience issues.
  • Collaborate with cross-functional teams like Algorithm, Product, Engineering, Legal teams, etc.

; to implement measures enhancing ecosystem health.

  • Monitor the health of the ecosystem through data-driven and investigative methods; respond to emergencies, conduct ad-hoc investigations, and take action as needed.
Qualifications

Minimum Qualification(s)

  • 5+ years of demonstrated leadership experience in data-driven anti-fraud and governance and experience programmes within O2O, Local Services, E-commerce, or related fields.
  • Strong Bachelor's degree and above, preferably in a quantitative field such as Mathematics, Statistics, Engineering, Data Analytics, or related fields.
  • Proficiency in utilising querying and analytical tools, and conducting data analysis (e.g., SQL, Python, Excel) is advantageous.

Data interpretation or analysis is necessary for this role.

  • Possesses strategic thinking & programme management skills.

Able to manage and push complex projects, and influence cross-functional teams.

  • Excellent English oral and written communication skills, including a demonstrated ability to develop and communicate complex strategies in writing.

Preferred Qualification(s)

  • Proactive, independent and driven; able to thrive in ambiguity and handle multiple competing priorities in a fast-paced environment.

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Company profile

TikTok

Online Media & eCommerceMore than 10,000 employees

TikTok is the world's leading destination for short-form video. Our platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible.

Our employees lead with curiosity, and move at the speed of culture. Combined with our company's flat structure, you'll be given dynamic opportunities to make a real impact on a rapidly expanding company as you grow your career. We have offices across Asia Pacific, the Middle East, Europe, and the Americas – and we're just getting started.

Perks and benefits
Medical
Education support
Dental
Vision

Company information

Registration No.201719908M

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