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Job Responsibilities:
Job Description:
We are seeking a motivated and detail-oriented Data Scientist to join our analytics and AI team. This role is ideal for candidates with foundational experience in data science and a strong interest in applying machine learning, statistical techniques, and scalable data tools to real-world problems. You will collaborate with data scientists and engineers to develop, deploy, and monitor data-driven solutions.
Key Responsibilities:
Assist in designing and implementing machine learning models for predictive analytics and anomaly detection
Perform statistical analysis to extract insights and support business decisions
Collaborate with cross-functional teams to understand data requirements and deliver actionable solutions
Contribute to data preprocessing, feature engineering, and model evaluation
Support the deployment and monitoring of models in production environments
Use Databricks for scalable data processing and model development
Required Qualifications:
Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field
Hands-on experience with Python and machine learning libraries
Understanding of statistical methods and their application in data analysis
Good communication and collaboration abilities
Fluency in English
Preferred Qualifications:
Familiarity with cloud-based platform especially Databricks
Hands-on experience with ML monitoring tools (e.g., MLflow).
Knowledge of SQL and data visualization tools
Experience with PySpark
Internship or academic project experience in data science or machine learning
Work experience:
Above 5 years of experience.
At Magna, we believe that a diverse workforce is critical to our success. That’s why we are proud to be an equal opportunity employer. We hire on the basis of experience and qualifications, and in consideration of job requirements, regardless of, in particular, color, ancestry, religion, gender, origin, sexual orientation, age, citizenship, marital status, disability or gender identity. Magna takes the privacy of your personal information seriously. We discourage you from sending applications via email or traditional mail to comply with GDPR requirements and your local Data Privacy Law.
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