Senior Data Scientist

About

Are you a data scientist, and love what you do? Would you like to be a part of a global customer facing Team focused on solving complex, real-world business problems? Would you like to be a part of a community of technical leaders, highly specialised in their disciplines and working together as one to bring the best practices of engineering and architecture to world’s largest enterprise customers? The Industry Solutions Delivery (ISD) Engineering & Architecture Group (EAG) is a global consulting and engineering organization that supports our most complex and leading-edge customer engagements.

Responsibilities

• 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.
• Embody our culture and values.

Requirements

• 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: Agentic AI, GenAI, AI native development, Computer Vision, LLMs, Audio/Voice data processing, and Reinforcement Learning and consulting experience.
• 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) and consulting experience.
• 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) and consulting experience.
• OR Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, Engineering or related field and consulting experience.
• OR equivalent experience.
• Business language proficiency in both Korean and English.

Preferred

• 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, AgentOps and frameworks like LangChain, Semantic Kernel and MCP.
• 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.
• Experience designing AI Skills (Skill.md or equivalent capability definitions) that encapsulate domain knowledge, business workflows, reasoning strategies, and tool integrations for Agentic AI solutions.

Benefits

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