Job description
Overview
Our client is a global technology and manufacturing leader specialising in advanced memory and storage solutions. The organization is known for its strong focus on innovation, operational excellence, and data‑driven decision‑making across large‑scale manufacturing environments.
As a Data Science Engineer, you will apply advanced techniques from mathematics, statistics, operations research, and software engineering to extract insights from complex manufacturing and operations data. You will play a key role in developing predictive models, digital twin solutions, optimization frameworks, and analytics tools that improve production metrics and planning decisions across global manufacturing operations.
Responsibilities
- Design, develop, and implement data science, simulation, and optimization solutions to analyze large, diverse, and unstructured datasets.
- Build software programs, algorithms, and automated processes to cleanse, integrate, and evaluate data from multiple disparate sources.
- Collaborate with product, service, engineering, and UX teams to identify high‑impact business questions, define experiments, and drive analytical projects.
- Develop and enhance manufacturing digital twin and discrete event simulation models to support planning and operational decision‑making.
- Apply optimization and operations research techniques (e.g., linear programming, mixed‑integer programming) to improve throughput, cycle time, and capacity utilization.
- Identify meaningful insights and patterns from large data and metadata sources.
- Interpret analytical results and communicate findings clearly to technical and non‑technical stakeholders.
- Explore and apply emerging tools, technologies, and methodologies to enable innovative and scalable solutions.
- Work with management, cross‑functional teams, and global manufacturing sites to identify optimization opportunities and continuously improve production metrics.
- Drive global collaboration, alignment, standardization, and benchmarking of simulation and optimization solutions across planning and operations.
Qualifications
- Bachelor's degree in Computer Science, Data Science, Industrial Engineering, Operations Research, or a related field.
- At least 3 years of professional experience with demonstrated ability to quickly learn new programming languages and tools.
- Experience in manufacturing or semiconductor operations, preferably with exposure to digital twin solutions.
- Hands‑on experience with discrete event simulation in manufacturing or operations environments.
- Experience with optimization modeling and operations research techniques such as linear programming and mixed‑integer programming.
- Strong programming experience in Python, Java, SQL, along with exposure to C/C++ or similar languages.
- Familiarity with cloud technologies, APIs, ETL pipelines, and version control systems (e.g., Git).
- Strong problem‑solving skills with a structured, logical approach.
- Clear and effective communication skills, with the ability to translate complex analytical results into actionable insights.
