Microsoft Data Scientist II 

Taiwan, Taoyuan City 

317081144

Required/Minimum Qualifications:

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research).
• OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research).
• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field.
• OR equivalent experience.
• 1+ year(s) customer-facing, project-delivery experience, professional services, and/or consulting experience.

Other Requirements:

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:

Microsoft Cloud Background Check:

• This position will be required to pass the Microsoft background and Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Additional or Preferred Qualifications:

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research)
• OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research).
• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research).
• OR equivalent experience.
• 1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers).
• Familiarity with device fingerprinting, fuzzy ID techniques, or entity resolution.
• Experience in risk scoring, bot mitigation, or anomaly detection systems.
• Proficiency with cloud platforms such as Azure, and real-time inference systems.
• Communication and collaboration skills, with the ability to influence across disciplines.
• Proven ability to optimize detection systems for both technical and business metrics.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Microsoft will accept applications for the role until May 15, 2025.

As a Data Scientist II, you will:

• Understand where toacquirethe data necessary for your project plan and use querying, visualization, and reporting techniques to describe that data.You’ll

• Understand modeling techniques, select the correcttooland approach to completeobjectives, and evaluate the output for statistical and business significance.
• You’llanalyze model performance and incorporate customer feedback into its evaluation.

• Understand the current state of the industry, including current trends, so that you can contribute to thought leadership best practices.
• You’llalso write code for a specificfeature, anddevelop a workingexpertiseof proper debugging techniques.

• Understand device fingerprinting techniques,analyze the device attributes collectedfordevice fingerprinting, identify anomalous attributes within sessions as well as across sessions.
• You willdeveloptechniques to devise a unique device identifiergiven the device attributes

• Understand theend to endprocessesof the real timedecision platform, e.g., where theAPI is defined,what the API payload looks like, how wedo feature engineering,where we deploy our models,how wemonitor thedata flowandhow wemanage rules, among other things.

• andderive actionableinsightsvia data analysesto meet the goals.
• You will examine projects through a customer-oriented focus and manage customer expectationsregardingproject progress andwillpresentthefindingstobusiness stakeholders

• bestpractices foridentifyinggrowth opportunitiesand endeavor to stay current with thelatest trends in machine learning, fraud detection, and abuse prevention.