We are seeking a Data Scientist to lead data-driven initiatives in battery technology and manufacturing optimization. The ideal candidate has strong expertise in Azure Machine Learning, Python, and SQL, and is adept at delivering scalable, production-ready models in an Agile environment. This role requires cross-functional collaboration to drive measurable improvements in product performance and operational efficiency.
Key Responsibilities
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Design, develop, and deploy machine learning models to optimize battery materials, design, and production.
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Lead full-cycle data science projects in an Agile environment, from scoping to deployment and monitoring.
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Build data pipelines and RESTful APIs to enable scalable access to models and analytics.
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Create intuitive dashboards and reports using Power BI or similar tools for non-technical stakeholders.
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Collaborate with engineers, chemists, and IT to integrate data insights into R&D and production workflows.
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Monitor model performance using key metrics (e.g., yield improvement, cost savings, error rates).
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Ensure compliance with data governance, security, and regulatory standards.
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Follow best practices in testing, version control, and documentation.
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Stay updated on AI/ML trends and emerging technologies to drive innovation.
Required Qualifications
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Bachelor’s degree in Data Science, Computer Science, Engineering, or related field (Master’s preferred).
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5+ years of experience in data science, with hands-on ML model development and deployment.
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Proficiency in Python, SQL, and Power BI (or equivalent data visualization tools).
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Experience with Microsoft Azure Machine Learning and cloud-based development.
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Familiarity with RESTful APIs and software development lifecycle (SDLC).
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Strong communication, analytical, and problem-solving skills.
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Experience working in Agile teams, with familiarity in Scrum or Kanban methodologies.
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Bonus: Knowledge of Azure Cognitive Services, NLP, computer vision, or manufacturing analytics.
Penang, MY, Malaysia
