Data Scientist

About the role

This Data Scientist role at Magna focuses on enhancing automotive manufacturing through advanced data analytics. The work involves applying machine learning, AI, and computer vision to address challenges across product development, manufacturing, and predictive maintenance. A key aspect of the role is supporting the deployment and adoption of AI initiatives, from proof-of-concept to small-scale implementation.

The position requires conceptualizing machine learning problems, exploring various theoretical approaches, and executing simulations with minimal oversight. The Data Scientist will also be responsible for interfacing with senior management to provide regular project updates. This indicates a need for clear communication and the ability to translate technical work into business insights.

Success in this role means leveraging internal and external expertise to drive innovation within Magna's operations. The individual may also occasionally supervise indirect hires like summer students, suggesting a potential for mentorship and leadership within specific project contexts. The company emphasizes its global, entrepreneurial team and 65 years of expertise in advancing mobility.

The compensation for this role is listed at 90,000 USD.

Skills that matter here

• Python: This role requires strong proficiency in Python for statistical analysis, machine learning, and developing data-driven solutions.
• Machine Learning: The Data Scientist will apply a broad range of machine learning techniques to solve manufacturing challenges and improve processes.
• Computer Vision: Computer vision is a key tool for this role, used to enhance manufacturing operations and address specific project challenges.
• Microsoft Azure: Familiarity with cloud platforms like Microsoft Azure is necessary for data management and processing in this role.
• PySpark: Experience with PySpark is required for data management and processing tasks within the manufacturing environment.
• JIRA: Working knowledge of JIRA is needed for collaboration and project tracking within an agile development framework.

Who this role suits

• A self-motivated individual who is curious and enjoys collaborative problem-solving.
• Someone who is willing to continuously learn, ask questions, and build strong relationships across teams.
• A person comfortable with minimal supervision who can independently conceptualize and implement machine learning solutions.
• An effective communicator capable of presenting project updates to senior management.

From the employer

• Support development of data analytics projects, apply data science, analytics, and computer vision to solve challenges in the manufacturing environment.
• Execute strategy and support applications of statistical analysis, Machine Learning, Computer vision, and AI tools to improve product development, manufacturing, predictive maintenance, and business processes.
• Support, plan, and execute the initial and wider deployment and adoption of ML and AI initiatives, PoC, and small-scale implementation.
• Conceptualize Machine Learning problems, apply appropriate theory, explore approaches, execute simulations, and implement with minimal supervision.
• Leverage internal and external expertise as required.
• Regularly interface with senior management to provide project updates.
• Occasionally responsible to hire, lead, supervise, and evaluate indirect hires, such as summer students.

• Experience with a broad range of machine learning and AI techniques, including computer vision and deep learning (e.g., TensorFlow).
• Strong proficiency in Python for statistical analysis, machine learning, and data‑driven solution development; working knowledge of C++.
• Experience with data management and processing using PySpark and SQL.
• Familiarity with cloud platforms and tools such as Microsoft Azure, AWS, and Databricks.
• Experience working in agile environments, including tools such as JIRA and Confluence, and DevOps practices (Git, Docker, CI/CD).
• Self‑motivated, curious, and collaborative, with a willingness to learn, ask questions, and build strong cross‑functional relationships.

• Hybrid work policy.
• Wellness programs and events.
• On-site cafeteria.
• Parking for electric vehicles.
• Access to private park for employees & their families.