jobs in OSRAM Opto Semiconductors (Malaysia) Sdn. Bhd., Penang

Kerja Sepenuh Masa, Data Science Senior-Staff Engineer di OSRAM Opto Semiconductors (Malaysia) Sdn. Bhd., Penang Pulau Pinang - Maukerja

Data Science Senior-Staff Engineer

OSRAM Opto Semiconductors (Malaysia) Sdn. Bhd., Penang

Kongsi
Simpan

Lokasi Kerja

  • Bayan Lepas Pulau Pinang Malaysia

Penerangan Kerja

Tanggungjawab

Sense the power of light

The ams OSRAM Group is a global leader in innovative light and sensor solutions. With more than 110 years of industry experience, we combine engineering excellence and global manufacturing with a passion for cutting-edge innovation enabling transformative advancements in the automotive, industrial, medical, and consumer industries. “Sense the power of light” – our success is based on the deep understanding of the potential of light and distinct portfolio of emitter and sensor technologies. Around 19,700 employees worldwide drive innovations alongside societal megatrends. Find out more about us on *************


The ams OSRAM Opto Semiconductors business offers high-performance opto semiconductor components and in-depth support for state-of-the-art system solutions based on innovative semiconductor light sources. The Business Unit can look back on almost fifty years of production and development expertise.

Your new responsibilities

  • Conduct data‑centric evaluations and analytical studies to support R&D projects/initiatives, technology development and/or validation activities.
  • Collaborate with cross‑functional R&D teams to translate engineering and/or scientific ideas/problems into analytical solutions.
  • Perform data-driven asset utilization using Cloud/Big‑Data technologies to enable scalable data exploration, processing and advanced analytics.
  • Generate clear and impactful visualizations, dashboards and analytical reports to communicate findings to technical and non‑technical stakeholders.
  • Ensure data quality, consistency, and traceability through sound data management and governance practices.
  • Contribute to the continuous improvements of data science methodologies, tools, and best practices within the R&D environment.


What we look for


  • Bsc/MSc/PhD in Data Science, Statistics, Computer Science, Applied Mathematics, Physics, Engineering or a related quantitative field.
  • Experience working in R&D/technology-driven environments (e.g., engineering, manufacturing, electronics) with a strong focus on measurable business impact.
  • End-to-end analytics project experience: data sourcing/ETL, feature engineering, modeling, deployment/automation and stakeholder reporting; familiarity with agile ways of working.
  • Primarily an individual contributor with the ability to lead workstreams, mentor junior colleagues and influence cross-functional teams without formal authority.
  • Comfortable collaborating in global, multicultural teams across sites and time zones; experience working with international stakeholders is a plus.
  • Strong foundation in statistics and machine learning (regression/classification, time-series, clustering, optimization), experimental design and model validation, etc.
  • Structured problem solving (hypothesis-driven analysis/CRISP-DM), reproducible analytics, documentation and peer review; data quality checks and governance/traceability practices, etc.
  • Python (pandas, NumPy, scikit-learn) and/or SQL required; Big Data tools (Spark/Databricks) and Cloud platforms (Azure/AWS/GCP) preferred; Git, APIs, Docker/CI-CD basics; Power BI/Tableau for dashboards, etc.
  • English – fluent (spoken and written). Additional local language(s) beneficial.
  • Excellent communication and data storytelling, strong collaboration and stakeholder management, curiosity and learning agility, able to translate engineering problems into analytical solutions, etc.
  • High standards for confidentiality and handling sensitive data; proactive continuous-improvement mindset, willingness to travel if needed, etc.


Please contact Nurul Ain Rosli for further information via ************* or +60 *************.

Peringatan Penting

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