Team Intro

At Tik Tok, we're committed to a process of continuous innovation and improvement in our user experience and safety controls. We're proud to be able to serve a global community of more than a billion people who use Tik Tok to creatively express themselves and be entertained, and we're dedicated to giving them a platform that builds opportunity and fosters connection. We also take our responsibility to safeguard our community seriously, both in how we address potentially harmful content and how we protect against unauthorized access to user data.

Our US Data Security Safety team provides key support for Tik Tok's innovative initiatives, state-of-the-art products, and integrated platforms servicing our US market. As a Data Scientist on Tik Tok's US Data Security Safety Product team, you will be instrumental in ensuring that Tik Tok remains a safe, trustworthy, and risk-free environment to create and enjoy content across all of our apps while protecting our brand.

The ideal candidate will have a background in a statistics and product analytics, will have experience working with large data sets, and will have some experience delivering data products on a fast-paced team.

This Senior Data Scientist may be exposed to harmful content as part of their core day-to-day functions, as well as in project work; in response to escalation requests; or by chance.

Some content viewed my violate our community guidelines which include but are not limited to bullying; hate speech; child abuse; sexual assault; torture; bestiality; self-harm; suicide; and murder.

This position will be full-time and will be based in our San Jose location.

Responsibilities

• Partner with product, operations, policy, and engineering teams to scope, design, execute, measure, and improve the impact of US Safety efforts
• This individual will break down the hairiest of problems by applying the full data science toolkit and provide insights to stakeholders across the organization to change minds and hearts
• Be constantly curious and continue to pursue in-depth explorations of our datasets and business
• Conduct quantitative analysis, deliver insights, and influence US Safety decision making through understanding of user behavior and safety ecosystem
• Independently design, research, develop and apply ML/AI solutions to solve business problems, including prediction, optimization, segmentation and so on
• Deep understanding of our organization's data structure; look for ways to improve to enhance our ability to perform robust data analysis; create new data sets when there is little or no data available, to inform marketing analysis
• Design and monitor core metrics; perform root cause analysis to explain drivers
• Identify trends and opportunities to drive safety initiatives and create a healthy ecosystem for content creators, users, and consumers
• Collect and provide quantitative and qualitative information to measure risk of feature/product launches and answer strategic business questions

Qualifications

Minimum Qualifications

• Ph.D., M.S., or Bachelors degree in Computer Science, Data Science, Mathematics/Statistics and other STEM majors is required
• Over 5+ years of industry experience in data science, data analytics, product analytics, quantitative analysis and machine learning experience to build ML-driven products for solving business problems
• Experience with experimentation and testing of Minimum Viable Products to determine if proposed business models / solutions scale up
• Experience in utilizing SQL/Python to extract, manipulate, and analyze datasets
• Experience with creating data visualizations to communicate metric performance
• Experience with statistical analysis or data modeling techniques, including: hypothesis testing, experiment design, and common regression and classification algorithms
• Experience building data infrastructure and implementing reporting solutions

Preferred Qualifications

• 4 or more years of experience as a Product or Applied Data Scientist
• Your ability to work in a high tempo environment, adapt, respond to day-to-day challenges of the role
• Your resilience and commitment to self-care to manage the emotional demands of the role
• Previous experience in data science, data analytics, or product analytics at a consumer technology company
• Passion for social technology products and a curiosity to learn and grow with a fast paced company
• Experience working with international partners in different time zones

Compensation

The base salary range for this position in the selected city is $144,000 - $329,334 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

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.

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
3. Exercising sound judgment