Senior Data Scientist

Required/Minimum Qualifications 

• Minimum of 8 years (for those with Bachelor’s Degree / Master’s Degree) or 5 years (for those with a Doctorate) of experience as a data scientist implementing data science solutions, with experience in implementing projects in one or more areas amongst: Computer Vision, LLMs, Audio/Voice data processing, and Reinforcement Learning.  
• Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, Engineering or related field AND data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)  
  • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, Engineering or related field data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience. 
  • OR Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, Engineering or related field 
• OR equivalent experience.  

• Business level Japanese and English language skills. 

Your success in this role will be achieved if you are comfortable interacting with external customers, are able to manage a complicated internal stakeholder group, and can demonstrate the following key knowledge, skills and experience:   

• Hands-on software engineering experience (e.g. Python, C++).  

• Proven skills and experience in a data science role.   

• Familiarity with building and deploying largescale AI solutions into production within a cloud environment. Has experience in working with MLOps, LLMOps and frameworks like LangChain, Semantic Kernel and Prompt Flow. 

• Experience of working with customers, directly and independently, in ensuring that the proposed solution addresses the business needs – through all stages from solutioning to deployment into production.  

Business Understanding and Impact:  

Guides and ensures good practice on engagements that employ data science to align with business needs and deliver value. Provides thought leadership and guidance to software engineering and business stakeholders on how to best include artificial intelligence and machine learning in systems development.  

Data Preparation and Understanding:  

Leads data acquisition and understanding efforts for engineering projects using various tools and techniques that support the data science lifecycle.

Modeling and Statistical Analysis:  

Develops and applies ML frameworks and best practices for scalable and ethical solutions.  

Evaluation:  

Oversees review of data analysis and modelling techniques. Ensures selected modelling techniques are appropriate and align with desired project outcomes. Decides on next steps (e.g., deployment, further iterations, new projects).  

Industry and Research Knowledge/Opportunity Identification:  

Provides feedback, drives improvement, and shares knowledge as a data science expert. Contributes to ongoing team learning by bringing relevant and leading edge concepts and approaches to the teams attention.  

Coding and Debugging  

Writes efficient, readable, extensible code from scratch that spans multiple features/solutions. Develops technical expertise in proper modeling, coding, and/or debugging techniques such as locating, isolating, and resolving errors and/or defects. Understands the causes of common defects and uses best practices in preventing them from occurring.  

Business Management  

Collaborates with end customer and Microsoft internal cross-functional stakeholders to understand business needs. Formulates a roadmap of project activity that leads to measurable improvement in business performance metrics over time.  

Customer/Partner Orientation  

Applies a customer-oriented focus by understanding customer needs and perspectives, validating customer perspectives, and focusing on broader customer organization/context. Promotes and ensures customer adoption by delivering model solutions and supporting relationships.