Data Science Manager - Manufacturing Data (KR)

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.