Responsibilities
Team Intro
The Global Payment team of U.S. Data Security department of TikTok provides payment solutions - including payment acquisitions, disbursements, transaction monitoring, payment method management, foreign exchange conversion, accounting, reconciliations, and so on - to ensure that users have a smooth and secure payment experience on TikTok platform. The team is also responsible for building data science and machine learning solutions to optimize our payment services leveraging large scale datasets and advanced algorithms. These solutions are key components for various business use cases, such as financial risk, payment compliance, marketing growth, and more.
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.
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Responsibilities:
You will be responsible to design and build advanced data science and algorithm solutions to solve interesting and impactful business problems, such as fraud prevention, AML, user experience customization and optimization, campaign management, etc.
Detailed job responsibility includes:
-Understand the payment business, translate business problems into data science and algorithm solutions where it fits
-Apply cutting edge machine learning technologies in various payment business use cases
-Own end to end model solution lifecycle and work with stakeholders to deliver business impact
-Improve modeling infrastructures, labels, features, and algorithms towards robustness, automation, and generalization
-Up-level risk machine learning excellence in privacy/compliance, interoperability, risk perception, and analysis
Qualifications
Minimum Qualifications:
- 3+ years of applied machine learning experience preferably in risk management or trust&safety
-Bachelor's degree or above in Computer Science/Statistics/Mathematics or other related majors
-Proficient in data processing and analytics in big data environment using SQL/Hive/Spark etc
-Mastery of at least one prevalent programming language for data science, such as Python, Java, or Scala
Preferred Qualifications:
-Experienced in Machine Learning and Deep Learning algorithms
- Experience with LLM, its application and custamization
- Working experience in the payment and fintech industry
Job Information
[For Pay Transparency] Compensation Description (annually)
The base salary range for this position in the selected city is $137750 - $237500 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.