Data Scientist (Content Ecology & Creator) - E-commerce Governance

Do

1. Governance Strategy & Risk Mining

• Pattern Discovery: Deep dive into creator behaviors and content logs to identify new abuse patterns (e.g., automated spam, matrix accounts, engagement farming).
• 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 Creator Governance, such as "Low-Quality Content Rate," "Creator Violation Rate," and "Ecosystem Health Index."
• Dashboarding: Build and maintain comprehensive data dashboards (using Tableau, Metabase, or internal tools) to visualize risk trends, strategy performance, and daily operational status.
• Automated Monitoring: Design alert systems that automatically flag anomalies in the data (e.g., a sudden spike in new account registrations or a drop in high-quality content supply).

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 creators.
• 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
• 1+ 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 Content 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

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $129960 - $246240 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

For Los Angeles County (unincorporated) Candidates:

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;

2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and

3. Exercising sound judgment.