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Position: Lead Data Scientist - Risk Data Mining
Institution: ByteDance
Location: Mountain View, California, United Kingdom
Duties: Build rules, algorithms and machine learning models, to respond to and mitigate business risks in ByteDance products/platforms. Such risks include and are not limited to abusive accounts, fake engagements, spammy redirection, scraping, fraud, etc; 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
Requirements: Bachelor or degrees above in computer science, statistics, math, internet security or other relevant STEM majors (e.g. finance if applying for financial fraud roles); Proficiency in data science analytical tools, such as SQL, R and Python; 4+ years of strong industry experience in relevant data mining domains. Example topics include (not limit to): search and ranking, recommendation, ads, anti-fraud/abuse, financial risk control. Good at telling data stories
   
Text: Teams Locations Blog Students & Grads Jobs Lead Data Scientist - Risk Data Mining Mountain View R&D - Security Experienced Job ID: J1V7P Responsibilities Founded in 2012, ByteDance is a technology company operating a range of content platforms that inform, educate, entertain and inspire people across languages, cultures and geographies. With a suite of more than a dozen products, including TikTok, Douyin, Toutiao, Helo and Resso, ByteDance now has a portfolio of applications available in over 150 markets and 75 languages. The Business Risk Integrated Control (BRIC) team is missioned to: - Protect ByteDance 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 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 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. Responsibilities - Build rules, algorithms and machine learning models, to respond to and mitigate business risks in ByteDance products/platforms. Such risks include and are not limited to abusive accounts, fake engagements, spammy redirection, scraping, fraud, etc. - 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. - Own technical measurement and reduction of risk level of a specific business area (e.g. short video platform, growth, live streaming, ads, e-commerce, 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 Qualifications: - Bachelor or degrees above in computer science, statistics, math, internet security or other relevant STEM majors (e.g. finance if applying for financial fraud roles). - Proficiency in data science analytical tools, such as SQL, R and Python. - 4+ years of strong industry experience in relevant data mining domains. Example topics include (not limit to): search and ranking, recommendation, ads, anti-fraud/abuse, financial risk control. Good at telling data stories. - Solid experience in being tech leads or DS managers. Possess at least one advantages among risk control, mordern machine learning, 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. ByteDance is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At ByteDance, our mission is to inspire creativity and enrich life. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We believe individuals shouldn't be disadvantaged because of their background or identity, but instead should be considered based on their strengths and experience. We are passionate about this and hope you are too. ByteDance is committed to providing reasonable accommodations during our recruitment process. If you need assistance or an accommodation, please reach out to us at USRC@bytedance.com. Share to Contact us: Website Support Interview Feedback Related website: ByteDance | Careers at TikTok | Careers in China Follow us:youtube Privacy Policy ByteDance © 2020 English|日本語 - Bachelor or degrees above in computer science, statistics, math, internet security or other relevant STEM majors (e.g. finance if applying for financial fraud roles). - Proficiency in data science analytical tools, such as SQL, R and Python. - 4+ years of strong industry experience in relevant data mining domains. Example topics include (not limit to): search and ranking, recommendation, ads, anti-fraud/abuse, financial risk control. Good at telling data stories.
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