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Principal Data Scientist - Marketing Platform (Bangkok Based - Relocation Provied)

Recruitis Bangkok, Thailand

Human Resources Services · 11-50 employees

3 h ago
data-scientist Principal (10+ yrs) Full-time Visa sponsorship Thailand
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About the role

Lead the design and improvement of machine learning-powered solutions in a production environment to solve complex, real-world problems. Collaborate with cross-functional teams to define priorities, build robust experimentation methods, and ensure the scalability and quality of AI systems.

What they look for

Machine Learning Data Science LLM Prompt Design Retrieval Strategies Experimentation Design Model Evaluation Statistics Software Engineering Python Data Analysis System Optimization Production Environments Cross-functional Collaboration Technical Leadership Performance Analysis

Requirements

Requires extensive experience in a senior data science or machine learning engineering role with a strong background in end-to-end ML initiatives. Candidates must possess advanced skills in statistics, model evaluation, and production-level software engineering, ideally supported by an advanced degree in a quantitative field.

Full description

Who is our client?

Our client is a large-scale technology organization with a strong focus on engineering, data, and AI. They are continuing to invest in AI/ML platform capabilities that enable teams to build, operate, and scale machine learning and intelligent applications more effectively.

About the Role

This role is for a senior individual contributor who will lead the design and improvement of machine learning-powered solutions in a production environment. You will work on complex user-facing AI systems, drive experimentation and model improvement, and collaborate closely with cross-functional teams to turn ambiguous problems into practical, scalable solutions.

Responsibilities

  • Lead the development and enhancement of machine learning-based solutions for complex, real-world use cases
  • Translate open-ended product or user problems into clear data science approaches, experiments, and deliverable outcomes
  • Design, test, and refine prompts, retrieval strategies, evaluation frameworks, and model behaviors to improve quality and reliability
  • Build robust experimentation methods to assess model performance and compare alternative approaches
  • Work closely with product, engineering, analytics, and other technical teams to define priorities and drive implementation
  • Take ownership of solution quality across the lifecycle, from early exploration through deployment and iteration
  • Use data-driven methods to identify opportunities for model improvement, user impact, and system optimization
  • Contribute to the design of scalable workflows, including evaluation pipelines, monitoring approaches, and feedback loops
  • Communicate findings, trade-offs, and recommendations clearly to both technical and non-technical stakeholders
  • Support strategic decisions on model quality, scalability, performance, and long-term maintainability
  • Provide senior-level guidance in solving ambiguous AI problems with practical and measurable outcomes

Qualifications

  • Proven experience in a Staff Data Scientist, Applied Scientist, ML Engineer, or similar role, with strong ownership of end-to-end ML or LLM initiatives
  • Strong hands-on experience with machine learning platforms in production settings, including experimentation, evaluation, iteration, and quality improvement
  • Solid background in machine learning, statistics, and data science fundamentals
  • Experience applying quantitative methods to solve complex product or system problems at scale
  • Strong coding ability and practical experience working closely with software engineering teams in production environments
  • Experience building or improving systems that involve prompt design, retrieval, ranking, response quality assessment, or model evaluation
  • Strong understanding of experimentation design, success metrics, offline and online evaluation, and performance analysis
  • Comfortable working with ambiguity and shaping loosely defined problems into structured analytical approaches
  • Able to communicate complex technical ideas clearly and influence cross-functional stakeholders
  • Experience operating in fast-paced, product-driven environments with high expectations for quality and execution
  • Advanced degree in a relevant field such as Computer Science, Machine Learning, Statistics, Mathematics, Engineering, or a related quantitative discipline is preferred

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