Job description
About our client
My client is a is a technology company operating a range of content platforms that inform, educate, entertain and inspire people across languages, cultures, and geographies.
About the role
In this team you'll have a unique opportunity to have first-hand exposure to the strategy of the company in key ecurity initiatives, especially in building scalable and robust, intelligent and privacy-safe, secure and product-friendly systems and solutions.
There 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.
Your responsibilities
Build rules, algorithms and machine learning models, to respond to and mitigate business risks in products/platforms.
Such risks include and are not limited to account integrity, scalper, deal-hunter, malicious activities, brushing, click-farm, information leakage 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.
Qualification
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).
Solid data science skills. Proficiency in statistical analytical tools, such as SQL, R and Python.
Familiarity with machine learning or social/content online platform analytics. Bonus given to proficiency in modern machine learning applications.
Ability to think critically, objectively, rationally. Reason and communicate in result-oriented, datadriven manner. High autonomy.
