About SK Battery America (SKBA) As the flagship entity of SK On and a leader in the electric vehicle (EV) battery manufacturing sector, SKBA is at the forefront of advancing high nickel technology. With an impressive revenue of $2 billion and dedicated team of over 3,000 employees, we provide high-energy density battery cells to top automotive brands like Ford, Volkswagen, and Hyundai Motors. SKBA's North American expansion is marked by strategic joint partnerships with industry giants such as Ford and Hyundai, underscoring our commitment to the evolving EV landscape.
Role and Responsibilities: FDC System Development & Implementation: Lead the development, testing, and deployment of AI and data-driven solutions for the Fault Detection & Classification system, specifically for early detection and analysis of process/equipment anomalies. SPC System Development & Implementation: Drive the development, testing, and rollout of AI and data-centric solutions for the Statistical Process Control system, aiming to manage variations for statistical quality control. Statistical Analysis & Optimization: Utilize AI algorithms and methods to develop statistical models that analyze, monitor, and control production processes to ensure quality. Predictive Analysis & Optimization: Harness AI tools and methods to develop predictive models that preempt process or equipment faults, ensuring maximum uptime and efficiency. Data Management & Analysis: Design and manage robust database structures catering to the FDC system, utilizing languages and tools like Python, SQL, and TensorFlow. User Experience & Interface Development: Devise intuitive AI-driven interfaces for system operators to swiftly identify and react to potential faults, ensuring seamless operational flow. Troubleshooting & Maintenance: Address FDC-related software challenges promptly and implement periodic system updates to guarantee optimized performance. Continuous Learning & Training: Remain at the forefront of evolving trends in AI, data engineering, and FDC technologies. Conduct relevant training sessions and lend unwavering support to teams. Skills and Qualifications: Bachelor's degree in IT, Computer Science, Data Science, or equivalent work experience combined with education. 3+ years of hands-on experience in AI modeling and data engineering, preferably within fault detection or similar systems. Mastery in programming, particularly in Python, SQL, R, and Java. Extensive knowledge in leveraging data tools such as TensorFlow, PyTorch, Hadoop, and Spark. Superior teamwork, collaboration, and communication acumen. Innate problem-solving capability with agility in dynamic scenarios. An analytical mindset with the ability to decipher complex statistical data.
