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About the Role
Lead and develop a team at the intersection of manufacturing, data science, and AI. Guide technical approaches and deliver reliable solutions for manufacturing use cases, combining people management with technical judgment.
Responsibilities
- Lead and develop data scientists through regular 1:1s, feedback, coaching, and performance management.
- Support hiring, onboarding, and capability development for the team.
- Set technical expectations and review data science, data engineering, and analytical work.
- Translate manufacturing and customer problems into technical plans, success criteria, and actionable analysis.
- Partner with Team Leads to align priorities, ownership, capacity, dependencies, and risks.
- Work with Product, AI/ML, Software Engineering, SRE, and customer-facing teams to deliver integrated solutions.
- Improve team practices for technical review, knowledge sharing, and continuous improvement.
- Surface team and delivery risks early and communicate them clearly to relevant stakeholders.
Requirements
- Bachelor’s degree in a technical or quantitative field, or equivalent practical experience.
- 8+ years of related experience in data science, applied machine learning, analytics, data engineering, or a related technical discipline, including substantial hands-on data science experience.
- 3+ years of experience leading or managing technical professionals and supporting their career growth.
- Strong technical judgment in data science, including problem framing, statistical analysis, evaluation design, and interpretation of results; able to review analytical and modeling approaches and guide trade-offs.
- Demonstrated ability to turn ambiguous problems into clear plans and outcomes.
- Strong communication and collaboration skills across teams and functions.
- Professional Korean and working English (confirm based on customer and team needs).
- Experience in semiconductor manufacturing, industrial AI, or manufacturing data.
- Experience delivering data science or AI solutions in customer or production environments.
- Familiarity with feature engineering, model evaluation, or manufacturing process analytics.
- Experience building team practices, hiring plans, or technical career development paths.
Skills
- Data Science
- Applied Machine Learning
- Analytics
- Data Engineering
- Statistical Analysis
- Problem Framing
- Evaluation Design
- Interpretation of Results
- Feature Engineering
- Model Evaluation
- Manufacturing Process Analytics
- Communication
- Collaboration
Experience Level
- 8+ years of related experience
- 3+ years of experience leading or managing technical professionals
Education Level
- Bachelor’s degree in a technical or quantitative field, or equivalent practical experience.