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Data Scientist - DCC, Data Acquisition

TikTok

Data Scientist - DCC, Data Acquisition

TikTok

Singapore

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Learning and development stipend

Flexible PTO policy

Remote work flexibility

Health, dental, and vision coverage

Required Skills

Apache Spark

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Tik Tok

Data Scientist

  • DCC, Data Acquisition

2 weeks ago• Singapore
Viewed on February 1, 2026
Apply on company site

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

View Company Profile:

Responsibilities:

AI is the new electricity and data is the energy for AI. Our core belief is that unstructured data contains the untapped wisdom of humanity - and by building the best AI-ready data infrastructure, we enable more meaningful, responsible, and creative uses of AI.

Data Cycling Center (DCC) is a Data Science team responsible for building the mid-platform data layer that powers AI development across all business lines of Tik Tok, including e-commerce, advertising, livestreaming, and emerging technologies. Our initiatives include:

  • Scaled human-in-the-loop (HITL) data processing, delivering cost-effective results at benchmark quality levels
  • Highly automated end-to-end data pipelines for AI-generated content (AIGC)
  • Comprehensive content understanding and insight generation systems

As a Data Scientist on the Supply team, you will drive data-informed strategies to understand user behavior and optimize engagement across our platform. You'll design experiments, build predictive models, and translate complex data patterns into actionable insights that influence product and business decisions.
This role sits at the intersection of behavioral analytics, experimentation, and product strategy. You'll work with large-scale datasets to uncover what drives user engagement, predict behavior patterns, and develop interventions that improve key metrics. Your work will directly impact how we grow and retain our user base.

Responsibilities:

  1. Opportunity Identification: Analyze user data and growth metrics to identify areas for improvement and expansion opportunities
  2. Market Research: Research industry benchmarks, competitor strategies, and best practices to inform growth initiatives
  3. Experimentation: Design, implement, and analyze A/B tests to validate growth hypotheses and measure impact of interventions
  4. Predictive Modeling: Build models to predict user outcomes such as engagement, retention, and churn
  5. Data Analysis: Independently analyze experiment results and user behavior data to extract actionable insights
  6. Strategic Recommendations: Provide data-driven recommendations for growth strategy optimization and iteration
  7. Cross-functional Collaboration: Partner with product, operations, and engineering teams to ensure seamless execution of growth initiatives
  8. Trend Monitoring: Stay current with market trends and industry developments to adapt strategies and maintain sustainable advantage

Qualifications:

Minimum Qualification(s):

  • Bachelor's degree in a quantitative field (Statistics, Economics, Computer Science, Data Science, Mathematics, or related); Master's preferred
  • Minimum 3 years of experience in data science or analytics roles
  • Strong proficiency in SQL and Python (or R) for data manipulation and analysis
  • Solid foundation in statistics: hypothesis testing, regression analysis, and experimental design
  • Experience designing and analyzing A/B tests
  • Ability to translate complex analysis into clear, actionable business recommendations

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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)

Company Videos

Hear directly from employees about what it is like to work at Tik Tok.
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Next Up Tik Tok Client Provided Video 101:20

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  • 02:18Working at Tik Tok- Get Ready With Ali01:20Tik Tok Client Provided Video 100:33Client Provided Video 2 - Tik Tok02:07Working at Tik Tok
  • Limitless Possibilities01:41Working at Tik Tok
  • Women's Community01:31Working at Tik Tok
  • Women's Empowerment01:45Working At Tik Tok
  • BLXCK01:27Working at Tik Tok
  • Diversity, Equity and Inclusion with BLXCK
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About TikTok

TikTok

TikTok

Late Stage

A short-form video entertainment app and social network platform

10,001+

Employees

Los Angeles

Headquarters

$220B

Valuation

Reviews

3.1

3 reviews

Work Life Balance

1.5

Compensation

2.0

Culture

1.2

Career

1.8

Management

1.0

5%

Recommend to a Friend

Pros

Limited positive feedback available

Company size allows for potential opportunities

Technology platform experience

Cons

Mass layoffs and poor handling of terminations

Unprofessional management and HR behavior

Exposure to traumatic content without adequate support

Salary Ranges

52 data points

Mid/L4

Senior/L5

Mid/L4 · Applied AI Product Data Scientist

1 reports

$273,000

total / year

Base

$210,000

Stock

-

Bonus

-

$273,000

$273,000

Interview Experience

4 interviews

Difficulty

3.5

/ 5

Duration

21-35 weeks

Experience

Positive 0%

Neutral 25%

Negative 75%

Interview Process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Interviews

6

Team Matching

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Data Structures