The Data Science Manager will lead and develop a team of data scientists to create AI-driven solutions for manufacturing challenges, translating customer problems into actionable technical plans. The role combines people management, hiring, and hands‑on technical oversight across data science, engineering, and analytics initiatives.
The Data Science Manager leads and develops a team working at the intersection of manufacturing, data science, and AI. You will help the team understand customer and product needs, guide technical approaches, and deliver reliable solutions for manufacturing use cases. This is a hands-on leadership role: you will combine people management with technical judgment while partnering closely with Team Leads and cross-functional teams.
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.
Help 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.
Basic Qualifications
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).
Preferred Qualifications
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.
[Interview process]
Application review - Phone interview - Virtual onsite interview - Core Value interview - CEO interview
