Responsibilities
About the team
The E-Commerce Risk Control team works to minimize the damage of inauthentic behaviors on Tiktok E-Commerce platforms, covering multiple classical and novel business risk areas such as account integrity, incentive abuse, malicious behaviors, brushing, click-farm, information leakage, 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, transferable, while still down to the ground to make quick and solid differences.
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Responsibilities:
- Build machine learning solutions to respond to and mitigate business risks in Tiktok products/platforms. Such risks include and are not limited to abusive account integrity, scalper, deal-hunter, malicious activities, brushing, click-farm, information leakage etc.
- Improve modeling infrastructures, labels, features and algorithms towards robustness, automation and generalization, reduce modeling and operational load on risk adversaries and new product/risk ramping-ups.
- Up-level risk machine learning excellence in privacy/compliance, interpretability, risk perception and analysis.
- Build fraud detection, anomaly detection, and risk-scoring models using supervised, unsupervised, and deep learning techniques.
- Apply graph-based models for detecting fraud networks
In order to enhance collaboration and cross-functional partnerships, among other things, at this time, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager/department. We regularly review our hybrid work model, and the specific requirements may change at any time.
Qualifications
Minimum Qualifications
- Master degrees in Computer science, Mathematics, Machine Learning, or other relevant STEM majors (e.g. finance if applying for financial fraud roles).
- Experience programming in Java, C++, Python or related language
- 3+ years of hands on experience in building and delivering machine learning models for large-scale projects.
- Track record of developing and implementing models and visualizations using programming and scripting (Scala, Python, R, Ruby, and/or Matlab).
- Strong understanding of anomaly detection, predictive modeling, and Bayesian inference.
- Experience with real-time ML systems, feature engineering, and risk scoring models.
- Experience using various forecasting, machine learning and statistical tools and communicating results, plans and/or risks clearly.
- Ability to think critically, objectively, rationally. Reason and communicate in result-oriented, data-driven manner. High autonomy.
Preferred Qualifications:
- A PhD in CS, Machine Learning, Statistics, Operations Research, or relevant field
- 4+ years of industry experience in predictive modeling and analysis
- Experience collaborating with product, operations and engineering teams is a plus.
- Excellent analytical and communication skills and ability to influence stakeholders.
- Experience in e-commerce / online companies in fraud / risk control functions
- Knowledge of explainable AI (XAI) techniques (SHAP, LIME)
Job Information
[For Pay Transparency] Compensation Description (annually)
The base salary range for this position in the selected city is $184300 - $337250 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.