Microsoft Principal Data Scientist - Azure Networking Security 

Taiwan, Taoyuan City 

617855851

• • Required:

    • 10+ years of industry experience in data science or related fields (e.g., managing structured and unstructured data, applying statistical techniques and reporting results), OR a PhD with 5+ years, OR a Master’s with 7+ years, OR equivalent experience.
    • Proven track record of delivering impactful data science solutions.
    • Experience with distributed computing platforms for high-scale systems and big data.
    • Strong data pre-processing skills.
    • Excellent collaboration and independent work capabilities.
    • Ability to learn and adopt new technologies quickly.

    Preferred:

    • Background in Networking, Application Security, or Data Security.
    • Experience with cloud-based applications, especially Microsoft Azure components and tools.
    • Familiarity with continuous integration and deployment tools (ADO preferred).
    • Experience working across geographically distributed teams.
    • Exposure to emerging technologies such as LLMs to enhance quality and efficiency.
    • Ability to execute in ambiguous environments with incomplete data.

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 Cloud Background Check upon hire/transfer and every two years thereafter.

• Build and Design: Develop and implement advanced data science models and algorithms to solve complex business problems. Utilize the latest AI tools and Large Language Models (LLMs) to handle vast amounts of data, ensuring scalability and efficiency. This includes designing robust data pipelines, performing exploratory data analysis, and deploying machine learning models into production environments.
• Innovation: Drive innovation by building and shipping software at scale. Continuously explore and integrate cutting-edge technologies and methodologies to enhance the team's capabilities and deliver impactful solutions.
• Collaboration: Work with cross-functional teams, including engineering, product management, and business stakeholders, to ensure successful project delivery. Foster a collaborative environment that encourages knowledge sharing and collective problem-solving.
• Lead and Mentorship: Serve as the organizational focal point for all Data Science projects. Mentor and guide junior team members to enhance their skills and knowledge, providing technical leadership and fostering a culture of continuous learning and improvement.
• Embody our