Data Science Lead, Quant Modeling

About the Team

The Product Data Analytics Team analyzes a combination of product usage and product performance data to derive meaningful insights that guide better product and decision-making for business leaders. As a member of the data science team, you will collaborate with diverse and highly collaborative teams of product managers, engineers, and other data analysts to drive product impact. You will work on exciting and challenging projects, converting insights into real changes for both new initiatives and scaled products. This role is ideal for a self-starter who is passionate about data, excels in product logic thinking, communicates clearly, and brings strong problem-solving skills and quantitative modeling experience.

Responsibilities

• Leverage data to solve challenging business problems across the full spectrum of product and business lines using analytical and statistical approaches.
• Build and improve statistical models (e.g., LTV and ROI prediction) to guide user growth-related decisions.
• Initiate model-driven analysis to provide deep insights into various products, identify common problem patterns, and establish inter-product analytic paradigms.
• Collaborate with Product, Operations, Engineering, and cross-functional teams to drive product development through analytic, statistical, and algorithmic expertise.
• Design, run, and analyze A/B experiments to inform and execute product strategy, ultimately improving the product and supporting business decisions.
• Design and monitor core metrics, identify root causes for metric movements through deep dives into models, and cover a wide range of model-driven solutions to deliver superior business outcomes.
• Leverage the causal structure of user behavior to identify trends and opportunities for user growth and ecosystem improvement, guiding the product team in decision-making.

Requirements

Minimum Qualifications

• Master’s degree in a quantitative discipline (e.g., Statistics, Operations Research, Computational Biology, Computer Science, Mathematics, Economics).
• 5+ years of experience in statistical modeling (Regression, Classification, Clustering, etc.) and machine learning (deep learning), including user-level modeling.
• Ability to conduct rigorous analysis and communicate conclusions to both technical and non-technical audiences.
• Proficiency in SQL, Python, or R.

Preferred Qualifications

• Solid communication and collaboration skills with the ability to work effectively in a diversified environment.
• Passion for the Internet industry and data analysis.
• Self-starter with the ability to acquire an in-depth understanding of the relationship between data and user experience/product growth.

About TikTok

TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, with additional offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Why Join Us

At TikTok, we create value for our communities, inspire creativity, and bring joy—a mission we work toward every day. We strive to do great things with great people, leading with curiosity, humility, and a desire to make an impact. Every challenge is an opportunity to learn and innovate as one team. We embrace an "Always Day 1" mindset, constantly iterating to achieve meaningful breakthroughs for ourselves, our company, and our users.

Pay

The base salary range for this position is $179,200 - $374,400 annually. Compensation may vary outside of this range depending on qualifications, skills, competencies, experience, and location. Base pay is one part of the total compensation package, which may also include discretionary bonuses, incentives, and restricted stock units.

Benefits

• Day-one access to medical, dental, and vision insurance.
• 401(k) savings plan with company match.
• Paid parental leave.
• Short-term and long-term disability coverage.
• Life insurance.
• Wellbeing benefits.
• 10 paid holidays per year.
• 10 paid sick days per year.
• 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.