Machine Learning Engineer/ Applied Data Scientist, E-Commerce Risk Control

• USDS

3+ months ago• San Jose, CA
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About Us

Tik Tok is the leading destination for short-form mobile video and our mission is to inspire creativity and bring joy.
Size: 5001-10000 employees

Industry: Entertainment & Gaming, Social Media, Technology

Responsibilities:

About the team
The E-Commerce Risk Control team works to minimize the damage of inauthentic behaviors on Tik Tok 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 zles -- 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.

Responsibilities:

• Invent, implement, and deploy cutting-edge machine learning algorithms, build prototypes, and explore entirely new conceptual solutions to respond to and mitigate business risks in Tik Tok e-commerce/platforms, including but not limited to fraudulent merchants, cheating influencers, malicious users, information security issues, and cross-domain risk challenges.
• Leverage techniques such as representation learning, graph models, deep learning, transfer learning, and multi-task learning to improve the efficiency of problem detection, thereby rapidly blocking risks and optimizing various metrics in the e-commerce community ecosystem.
• Monitor and attribute key metrics to quickly detect changes in risk and business trends, proactively identify potential attacks, continuously refine and adjust risk control strategies, and drive risk governance development and business model improvements.
• Mine and analyze massive e-commerce content and user behavior data to build both short-term and long-term user profiles, improve model precision and recall, and enhance robustness, automation, and generalization capabilities.
• Advance risk ML capabilities in

Qualifications

• Minimum Qualifications
• Master's degree in Computer Science, Mathematics, Machine Learning, or other relevant STEM disciplines.
• 2+ years of hands-on experience in building and delivering machine learning models for large-scale projects in internet companies.
• Proficiency in C++/Java/Python with strong coding skills, and familiarity with at least one common machine learning/deep learning platform.
• Deep understanding of supervised learning, unsupervised learning, and deep learning techniques, and the ability to build business algorithm models using relevant algorithms.
• Ability to think critically, objectively; reason and communicate in a results-oriented, data-driven manner; and work with high autonomy.

Preferred Qualifications:

• PhD in Computer Science, Machine Learning, Statistics, Operations Research, or related field.
• 4+ years of hands-on experience in building and delivering machine learning models for large-scale projects in internet companies.
• Experience in e-commerce/internet companies in fraud or risk control roles, with a track record of building fraud detection, anomaly detection, or similar risk control models using relevant algorithms.
• Ability to keep up with and proactively apply relevant technological advancements, incorporating the latest technologies (e.g., LLM, Multi-agent systems) into daily work.

Job InformationFor Pay Transparency Compensation Description (annually)

The base salary range for this position in the selected city is $136800 - $359720 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).

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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.

Client-provided location(s):San Jose, CA

Job ID: Tik Tok-7468510168017520914

Employment Type: OTHER

Posted: 2025-09-04T20:25:31
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Perks and Benefits

Health and Wellness

• Health Insurance
• Dental Insurance
• Vision Insurance
• HSA
• Life Insurance
• Fitness Subsidies
• Short-Term Disability
• Long-Term Disability
• On-Site Gym
• Mental Health Benefits
• Virtual Fitness Classes

Parental Benefits

• Fertility Benefits
• Adoption Assistance Program
• Family Support Resources

Work Flexibility

• Flexible Work Hours
• Hybrid Work Opportunities

Office Life and Perks

• Casual Dress
• Snacks
• Pet-friendly Office
• Happy Hours
• Some Meals Provided
• Company Outings
• On-Site Cafeteria
• Holiday Events

Vacation and Time Off

• Paid Vacation
• Paid Holidays
• Personal/Sick Days
• Leave of Absence

Financial and Retirement

• 401(K) With Company Matching
• Performance Bonus
• Company Equity

Professional Development

• Promote From Within
• Access to Online Courses
• Leadership Training Program
• Associate or Rotational Training Program
• Mentor Program

Diversity and Inclusion

• Diversity, Equity, and Inclusion Program
• Employee Resource Groups (ERG)

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