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Data Scientist Lead - TikTok BRIC (Singapore)

TikTok

Data Scientist Lead - TikTok BRIC (Singapore)

TikTok

Singapore

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Top Tier compensation with equity

Remote work flexibility

Wellness benefits

Flexible PTO policy

Learning and development stipend

Health, dental, and vision coverage

Required Skills

Apache Spark

TensorFlow

Airflow

Responsibilities

The Business Risk Integrated Control (BRIC) team is missioned to:

  • Protect Tik Tok users, including and beyond content consumers, creators, advertisers;
  • Secure platform health and community experience authenticity;
  • Build infrastructures, platforms and technologies, as well as to collaborate with many cross-functional teams and stakeholders.

The BRIC team works to minimize the damage of inauthentic behaviors on Tik Tok platforms (e.g. Tik Tok, Cap Cut, Lark), covering multiple classical and novel community and business risk areas such as account integrity, engagement authenticity, anti spam, API abuse, growth fraud, live streaming security and financial safety (ads or e-commerce), 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 privacy-safe, secure and product-friendly systems and solutions. Our challenges are not some regular day-to-day technical puzzles -- You'll be part of a team that's developing novel solutions to first-seen challenges of a non-stop evolvement of a phenomenal product eco-system. The work needs to be fast, transferrable, while still down to the ground to making quick and solid differences.

Key Responsibilities

  • Analyze business and security data, uncover evolving attack motion, identify weaknesses and opportunities in risk defense solutions, explore new space from the discoveries;
  • Define risk control measurements. Quantify, generalize and monitor risk related business and operational metrics. Align risk teams and their stakeholders on risk control numeric goals, promote impact-oriented, data-driven data science practices for risks. Detect abnormal changes in metrics and be able to build processes to analyze the root cause of such changes;
  • Design and build A/B experiments to satisfy various business needs. Build rules and models to respond to and mitigate business risks for different Tik Tok products. Such risks include and are not limited to abusive accounts, fake engagements, spammy redirection, scraping, fraud, etc.
  • Own technical measurement and evaluation of the risk level of a specific business area (e.g. short video platform, user growth, live streaming, etc). Define and coordinate planning, execution and generalization of risk solutions.
  • Drive and take responsibility for exercising data science best practices around risk analytics and modeling across all stakeholders. Leverage data to bridge the collaboration between such stakeholders.

Qualifications

Minimum Qualifications

  • Proficiency in data science analytical tools, such as SQL, R and Python.
  • Solid experience in leading complex and high impact DS projects. Possess at least one advantage among risk control, statistical problem solving, measurement-and-experiment-driven product iteration. Tracking records of making successful mid/long term technical strategic bets.
  • Strong ownership, proactive and skillful communication, ability to handle high complexity, urgency, cross-functional alignment.

Preferred Qualifications

  • Bachelor or degrees above in computer science, statistics, math, internet security or other relevant STEM majors.
  • 5 years of strong industry experience in relevant data science domains. Example topics include (but not limit to): search and ranking, recommendation, ads/monetization, anti-fraud/abuse, financial risks. Good at telling data stories.

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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