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.
