Data Science Senior/Staff Engineer

ams OSRAM is a global leader in innovative light and sensor solutions. “Sense the power of light” – our success is based on our deep understanding of the potential of light. By adding intelligence to light, we enable our customers to drive transformative applications. Our around 20,000 employees worldwide focus on innovation alongside the societal megatrends of digitalization, smart living, energy efficiency, and sustainability. Whatever your role is, you are a part of a talented team that enjoys exploring and designing new technologies.

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.

ams OSRAM is an Equal Employment Opportunity Employer. Diversity, equity and inclusion is strongly established in our corporate culture and we firmly believe it makes us more successful as a company. All qualified applications will receive consideration for employment regardless of ethnic, national or social origin, gender, gender identity, sexual orientation, color, religion, age, physical and mental abilities.

Information at a Glance Job ID: 23267 Posting Start Date: 4/23/26 Job Family: Research & Development Career Level: Professional (> 3 years) Company: OSRAM OS Penang Schedules: Full Time Work Model: Hybrid 40% Job Shift: Flex time Regular/Temporary: Regular Department: OS MY Systems, Test and Modeling

Application deadline: As long as the job is listed on our career page, we are looking for suitable candidates. We look forward to receiving your application.