Senior Data Scientist
Penang, MY, Malaysia
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ENOVIX Corporation
We are seeking a Senior Data Scientist to lead high-impact, data-driven initiatives in battery technology and advanced manufacturing optimization. This role is ideal for a seasoned professional with a strong background in manufacturing data science, Azure Machine Learning, and scalable model deployment. You will play a strategic role in shaping our data science roadmap, mentoring junior team members, and collaborating cross-functionally to drive measurable improvements in product performance, yield, and operational efficiency.
Key Responsibilities
- Lead end-to-end data science projects: from problem framing and data exploration to model development, evaluation, deployment, and monitoring.
- Design and implement predictive models, classification systems, clustering techniques, and anomaly detection algorithms to optimize battery materials and manufacturing processes.
- Partner with domain experts across engineering, R&D, manufacturing, HR, and finance to identify and prioritize high-impact use cases.
- Collaborate with Data Engineers to ensure scalable, maintainable data pipelines and AI workflows.
- Architect and deploy RESTful APIs and cloud-based ML solutions using Azure Machine Learning.
- Develop and maintain interactive dashboards and tools using Power BI, Python, and Azure analytics to deliver actionable insights.
- Mentor junior data scientists and analysts, fostering a data-driven culture and supporting team development.
- Support the build-out of the company’s AI strategy, including Agentic and Algorithmic AI frameworks.
- Ensure model governance, explainability, and compliance with standards such as SOC 2 and ISO.
- Track and report on key performance indicators (KPIs) such as yield improvement, cost savings, and predictive accuracy.
- Promote best practices in MLOps, including version control, testing, documentation, and monitoring.
- Stay current with emerging AI/ML trends and technologies relevant to manufacturing and battery innovation.
Required Qualifications
- Master’s or Ph.D. in Computer Science, Statistics, Data Science, Applied Mathematics, Engineering, or a related field.
- 6+ years of hands-on experience in data science, machine learning, or AI roles, with a strong focus on manufacturing or industrial applications.
- Proficiency in Python (including NumPy, pandas, scikit-learn, XGBoost, PyTorch/TensorFlow) and SQL.
- Experience with cloud-based analytics platforms such as Azure ML, Databricks, or Microsoft Fabric.
- Strong grasp of statistical modeling, time-series forecasting, classification, regression, and optimization techniques.
- Familiarity with MLOps practices and tools, including CI/CD for ML models.
- Ability to translate business problems into technical solutions and communicate effectively with non-technical stakeholders.
- Experience with RESTful APIs, software development lifecycle (SDLC), and Agile methodologies (Scrum/Kanban).
- Bonus: Experience with Azure Cognitive Services, NLP, computer vision, or predictive maintenance in manufacturing.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile AI strategy APIs Azure CI/CD Classification Clustering Computer Science Computer Vision Databricks Data pipelines Engineering Finance Industrial Kanban KPIs Machine Learning Mathematics ML models MLOps Model deployment NLP NumPy Pandas Pipelines Power BI Predictive Maintenance Python PyTorch R R&D Scikit-learn Scrum SDLC SQL Statistical modeling Statistics TensorFlow Testing XGBoost
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