Microsoft Data Scientist II 

Taiwan, Taoyuan City 

707175980

As a Data Scientist cum engineer you will need to build interactive dashboards and underlying schema. Additionally, design and build systems that allow LLMs to reason over large amounts of data as well as leveraging lighter weight models in place for specific scenarios. Partner with Stakeholders, PMs, and leadership teams to implement scalable data-driven frameworks for evaluating metrics and KPIs and build scalable Power-BI dashboards. Skills we are looking for are Kusto QL/KQL, SQL services, Power-BI, DAX, Function Apps, Data modelling, Azure Data Factory, etc.

• Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
• OR Master's Degree in Computer Science or related technical field AND 3+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
• OR equivalent experience.
• 3+ years of experience in machine learning.
• 3+ years using ML tools like Pytorch and TensorFlow.
• Practical experience developing applications using prompt engineering, fine tuning, Open AI or Azure Open AI APIs.
• System development skills, with a long-range system view that leverages development ranging from rapid research prototypes to carefully architected complex systems.

• Conduct applied science experiments, create and validate metrics, develop ML pipeline and modeling algorithm in the area of Large Language Models, Natural Language Processing, Information Retrieval, and Machine Learning.
• Prepare and manage data for project plans, proactively detect changes, and communicate updates to senior leads. Develop usable data sets, contribute to data ethics and privacy policies, and engage with customers about data integrity and cleanliness.
• Develop and deploy conversational and language understanding models at scale.
• Following and advancing best practices for Responsible AI and Privacy Preserving Machine Learning.
• Ensure models align with business goals, evaluate their effectiveness, design feedback methods, collaborate with engineers, and present findings to stakeholders.
• Provide technical feedback to the engineering team, identify business opportunities, propose collaborations, support strategy execution, leverage existing systems, share industry knowledge, and contribute to thought leadership and best practices.
• Collaborate closely with broader MS Security teams, Engineering and Partner/Product Groups, to create the next generation of products and services.
• Embody our and .