Job Summary

$7,500 - $15,000 SGD / Monthly EST

Job Type


Years of Experience
At least 2 years

Tech Stacks

Job Description

The Business Risk Integrated Control (BRIC) team is missioned:
- To protect ByteDance users, including and beyond content consumers, creators, advertisers;
- By securing platform health and community experience authenticity;
- Through building 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 ByteDance platforms (e.g. TikTok, CapCut, Resso, Lark), covering multiple classical and novel community and business risk areas such as account integrity, engagement authenticity, anti spam, API and growth health, 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.

- Enable and contribute to establishing fast and continuous threat response, in partnership with risk data scientists and product partners, by building advanced analytical tools and data insights.
- Enable and contribute to establishing robust, powerful and privacy-aware automated defense, in partnership with risk data scientists and infrastructure and platform partners, by creating and improving risk control rules, machine learning models and product initiatives.
- Enable and contribute to establishing scalable, reliable, generalizable and customizable risk detection and perception solutions that would be transferrable between products, markets and risk areas, which could help the future of risk data mining be more modulized, scalable beyond linear analytical head count.

- Bachelor or degrees above in Computer Science, Computer Engineering, Electrical Engineering, Statistics or other relevant majors (e.g. finance if applying for payment fraud positions).
- Solid technical / data-mining skills and ability to work with large volume data to identify and abstract abusive behaviour patterns in ByteDance products.
- Ability to think critically, to properly communicate problem challenges/solutions to, and to hold (as well as to be held) accountabilities on cross-functional partners in a clear, concise and timely manner.
- Strong ownership (proactivity, initiative, follows-through) to surface and solve open-ended problems against abusive attackers with adversarial nature.

- PhD degree in Computer Science or Statistics. Publications in top academic conferences on relevant data mining topics about social communities and content platforms (e.g. Botnet, interest group mining, fraud detection).
- 2+ years of industry experience (internship included) in predictive analytics and/or statistical modeling. Strong coding (backend, infra, algorithm) and system design background.
- Deep understanding about modern machine learning theory and applications, especially around popular neural nets (e.g. natural language processing, graph embedding), and/or relevant unsupervised/semisupervised/transfer learning. Hands-on industrial model development skills and strong data science sense/habit.

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