Data Scientist (Platform Governance), TikTok E-Commerce
Feb 5, 2026 Singapore
About us
TikTok is the leading destination for short-form mobile video and our mission is to inspire creativity and bring joy.
- Size: 10,000+ employees
- Industry: Technology: Consumer Internet
Why you should apply for a job to TikTok:
4.5/5 in overall job satisfaction
4.5/5 in supportive management
100% say women are treated fairly and equally to men
100% would recommend this company to other women
100% say the CEO supports gender diversity
Ratings are based on anonymous reviews by Fairygodboss members. See all reviews ›
Responsibilities
About the team
The Platform Governance team is focused to support the businesses by building an E-commerce ecosystem and improve platform service capabilities with the most advanced AI technology. We act as the strategists and health monitors of the ecosystem. We combine data analysis, machine learning, and metric construction to solve critical business problems.
Why this role?
Hybrid Impact: You won't just analyze data; you will build strategies (rules/models) to stop bad actors and design the metrics that guide the entire team.
Full Cycle Ownership: From discovering a new risk pattern -> building a detection strategy -> monitoring its success via dashboards.
Ecosystem Guardian: You will be the first to know when the ecosystem health fluctuates and the one who identifies why.
What You'll Do
1. Governance Strategy & Risk Mining
- Pattern Discovery: Deep dive into seller and listing behaviors to identify new abuse patterns.
- Strategy Construction: Translate insights into executable governance strategies using Rules, Thresholds, and Risk Scores. Quickly deploy tactics to mitigate sudden attacks.
- Practical Machine Learning: Develop agile, offline models (e.g., XGBoost, Random Forest, Anomaly Detection) and use Clustering to uncover organized bad-actor syndicates that simple rules might miss.
2. Metric System & Dashboard Construction
- North Star Definitions: Define and standardize core metrics for Seller and Listing Governance, such as "Low-Quality Listing Rate," "Listing Violation Rate," and "Bad seller On-boarding rate"
- Dashboarding: Build and maintain comprehensive data dashboards (using internal tools) to visualize risk trends, strategy performance, and daily operational status.
- Automated Monitoring: Design alert systems that automatically flag anomalies in the data .
3. Performance Tracking & Root Cause Analysis
- Strategy Evaluation: Continuously monitor the Precision and Recall of governance strategies. Analyze false positives to minimize impact on good sellers.
- Deep-Dive Analysis: When core metrics fluctuate (e.g., AIGC impact, GMV drops or complaint rates rise), conduct rapid root-cause analysis to determine if it is caused by governance interventions or external factors.
Qualifications
Minimum Qualifications:
- Bachelor's degree or above in computer science or related field
- Expert-level SQL is a must. You can handle massive, complex datasets efficiently
- Strong experience with BI/Dashboarding tools (e.g., Tableau, PowerBI, Metabase). You know how to design charts that tell a clear story
- Proficient in Python (Pandas, Scikit-learn). Hands-on experience with Tree-based models (XGBoost/LightGBM) and Unsupervised Learning (Clustering) for risk scoring and segmentation
- 2+ years of experience in Data Science, Analytics, or Risk Strategy
- You can explain complex data trends to non-technical stakeholders (Operations/Policy teams)
Preferred Qualifications
- Experience in Trust & Safety, Anti-Fraud, E-commerce Governance, or Listing Operations
- Experience building Metric Systems from scratch: knowing how to break down a high-level goal into trackable daily indicators
- You care about solving the business problem, not just using the most complex model
About the team
The Platform Governance team is focused to support the businesses by building an E-commerce ecosystem and improve platform service capabilities with the most advanced AI technology. We act as the strategists and health monitors of the ecosystem. We combine data analysis, machine learning, and metric construction to solve critical business problems.
Why this role?
Hybrid Impact: You won't just analyze data; you will build strategies (rules/models) to stop bad actors and design the metrics that guide the entire team.
Full Cycle Ownership: From discovering a new risk pattern -> building a detection strategy -> monitoring its success via dashboards.
Ecosystem Guardian: You will be the first to know when the ecosystem health fluctuates and the one who identifies why.
What You'll Do
1. Governance Strategy & Risk Mining
- Pattern Discovery: Deep dive into seller and listing behaviors to identify new abuse patterns.
- Strategy Construction: Translate insights into executable governance strategies using Rules, Thresholds, and Risk Scores. Quickly deploy tactics to mitigate sudden attacks.
- Practical Machine Learning: Develop agile, offline models (e.g., XGBoost, Random Forest, Anomaly Detection) and use Clustering to uncover organized bad-actor syndicates that simple rules might miss.
2. Metric System & Dashboard Construction
- North Star Definitions: Define and standardize core metrics for Seller and Listing Governance, such as "Low-Quality Listing Rate," "Listing Violation Rate," and "Bad seller On-boarding rate"
- Dashboarding: Build and maintain comprehensive data dashboards (using internal tools) to visualize risk trends, strategy performance, and daily operational status.
- Automated Monitoring: Design alert systems that automatically flag anomalies in the data .
3. Performance Tracking & Root Cause Analysis
- Strategy Evaluation: Continuously monitor the Precision and Recall of governance strategies. Analyze false positives to minimize impact on good sellers.
- Deep-Dive Analysis: When core metrics fluctuate (e.g., AIGC impact, GMV drops or complaint rates rise), conduct rapid root-cause analysis to determine if it is caused by governance interventions or external factors.
Minimum Qualifications:
- Bachelor's degree or above in computer science or related field
- Expert-level SQL is a must. You can handle massive, complex datasets efficiently
- Strong experience with BI/Dashboarding tools (e.g., Tableau, PowerBI, Metabase). You know how to design charts that tell a clear story
- Proficient in Python (Pandas, Scikit-learn). Hands-on experience with Tree-based models (XGBoost/LightGBM) and Unsupervised Learning (Clustering) for risk scoring and segmentation
- 2+ years of experience in Data Science, Analytics, or Risk Strategy
- You can explain complex data trends to non-technical stakeholders (Operations/Policy teams)
Preferred Qualifications
- Experience in Trust & Safety, Anti-Fraud, E-commerce Governance, or Listing Operations
- Experience building Metric Systems from scratch: knowing how to break down a high-level goal into trackable daily indicators
- You care about solving the business problem, not just using the most complex model
About the team
The Platform Governance team is focused to support the businesses by building an E-commerce ecosystem and improve platform service capabilities with the most advanced AI technology. We act as the strategists and health monitors of the ecosystem. We combine data analysis, machine learning, and metric construction to solve critical business problems.
Why this role?
Hybrid Impact: You won't just analyze data; you will build strategies (rules/models) to stop bad actors and design the metrics that guide the entire team.
Full Cycle Ownership: From discovering a new risk pattern -> building a detection strategy -> monitoring its success via dashboards.
Ecosystem Guardian: You will be the first to know when the ecosystem health fluctuates and the one who identifies why.
What You'll Do
1. Governance Strategy & Risk Mining
- Pattern Discovery: Deep dive into seller and listing behaviors to identify new abuse patterns.
- Strategy Construction: Translate insights into executable governance strategies using Rules, Thresholds, and Risk Scores. Quickly deploy tactics to mitigate sudden attacks.
- Practical Machine Learning: Develop agile, offline models (e.g., XGBoost, Random Forest, Anomaly Detection) and use Clustering to uncover organized bad-actor syndicates that simple rules might miss.
2. Metric System & Dashboard Construction
- North Star Definitions: Define and standardize core metrics for Seller and Listing Governance, such as "Low-Quality Listing Rate," "Listing Violation Rate," and "Bad seller On-boarding rate"
- Dashboarding: Build and maintain comprehensive data dashboards (using internal tools) to visualize risk trends, strategy performance, and daily operational status.
- Automated Monitoring: Design alert systems that automatically flag anomalies in the data .
3. Performance Tracking & Root Cause Analysis
- Strategy Evaluation: Continuously monitor the Precision and Recall of governance strategies. Analyze false positives to minimize impact on good sellers.
- Deep-Dive Analysis: When core metrics fluctuate (e.g., AIGC impact, GMV drops or complaint rates rise), conduct rapid root-cause analysis to determine if it is caused by governance interventions or external factors.
Qualifications
Minimum Qualifications:
- Bachelor's degree or above in computer science or related field
- Expert-level SQL is a must. You can handle massive, complex datasets efficiently
- Strong experience with BI/Dashboarding tools (e.g., Tableau, PowerBI, Metabase). You know how to design charts that tell a clear story
- Proficient in Python (Pandas, Scikit-learn). Hands-on experience with Tree-based models (XGBoost/LightGBM) and Unsupervised Learning (Clustering) for risk scoring and segmentation
- 2+ years of experience in Data Science, Analytics, or Risk Strategy
- You can explain complex data trends to non-technical stakeholders (Operations/Policy teams)
Preferred Qualifications
- Experience in Trust & Safety, Anti-Fraud, E-commerce Governance, or Listing Operations
- Experience building Metric Systems from scratch: knowing how to break down a high-level goal into trackable daily indicators
- You care about solving the business problem, not just using the most complex model
Responsibilities
ResponsibilitiesAbout the team
The Platform Governance team is focused to support the businesses by building an E-commerce ecosystem and improve platform service capabilities with the most advanced AI technology. We act as the strategists and health monitors of the ecosystem. We combine data analysis, machine learning, and metric construction to solve critical business problems.
Why this role?
Hybrid Impact: You won't just analyze data; you will build strategies (rules/models) to stop bad actors and design the metrics that guide the entire team.
Full Cycle Ownership: From discovering a new risk pattern -> building a detection strategy -> monitoring its success via dashboards.
Ecosystem Guardian: You will be the first to know when the ecosystem health fluctuates and the one who identifies why.
What You'll Do
1. Governance Strategy & Risk Mining
- Pattern Discovery: Deep dive into seller and listing behaviors to identify new abuse patterns.
- Strategy Construction: Translate insights into executable governance strategies using Rules, Thresholds, and Risk Scores. Quickly deploy tactics to mitigate sudden attacks.
- Practical Machine Learning: Develop agile, offline models (e.g., XGBoost, Random Forest, Anomaly Detection) and use Clustering to uncover organized bad-actor syndicates that simple rules might miss.
2. Metric System & Dashboard Construction
- North Star Definitions: Define and standardize core metrics for Seller and Listing Governance, such as "Low-Quality Listing Rate," "Listing Violation Rate," and "Bad seller On-boarding rate"
- Dashboarding: Build and maintain comprehensive data dashboards (using internal tools) to visualize risk trends, strategy performance, and daily operational status.
- Automated Monitoring: Design alert systems that automatically flag anomalies in the data .
3. Performance Tracking & Root Cause Analysis
- Strategy Evaluation: Continuously monitor the Precision and Recall of governance strategies. Analyze false positives to minimize impact on good sellers.
- Deep-Dive Analysis: When core metrics fluctuate (e.g., AIGC impact, GMV drops or complaint rates rise), conduct rapid root-cause analysis to determine if it is caused by governance interventions or external factors.
Qualifications
QualificationsMinimum Qualifications:
- Bachelor's degree or above in computer science or related field
- Expert-level SQL is a must. You can handle massive, complex datasets efficiently
- Strong experience with BI/Dashboarding tools (e.g., Tableau, PowerBI, Metabase). You know how to design charts that tell a clear story
- Proficient in Python (Pandas, Scikit-learn). Hands-on experience with Tree-based models (XGBoost/LightGBM) and Unsupervised Learning (Clustering) for risk scoring and segmentation
- 2+ years of experience in Data Science, Analytics, or Risk Strategy
- You can explain complex data trends to non-technical stakeholders (Operations/Policy teams)
Preferred Qualifications
- Experience in Trust & Safety, Anti-Fraud, E-commerce Governance, or Listing Operations
- Experience building Metric Systems from scratch: knowing how to break down a high-level goal into trackable daily indicators
- You care about solving the business problem, not just using the most complex model
Additional Information
- Posted: Feb 5, 2026