Seeking a Senior Data Scientist with extensive experience in the automotive sector. This role demands advanced skills in data modeling and mining, along with the ability to architect robust data frameworks for analytics and business intelligence. You will leverage machine learning algorithms for predictive modeling and enhance data-driven decision-making processes. Expertise in big data technologies is crucial for efficient data processing and analysis. Familiarity with generative AI tools will be key for innovation and improving model performance and insights.

Design and implement advanced data architecture frameworks to support analytics and business intelligence initiatives. Develop and deploy predictive models using machine learning algorithms. Analyze and process large datasets efficiently using big data technologies. Utilize generative AI tools to innovate and enhance model performance and data insights. Extract meaningful patterns and insights from complex data ecosystems. Ensure data integrity and reliability through strong data governance and quality principles.

Requires 6-10 years of experience in Data Science, preferably within the automotive domain. Possess advanced proficiency in data modeling and data mining techniques. Demonstrate deep understanding of machine learning algorithms and their practical applications. Showcase expertise in big data technologies and frameworks for efficient data analysis. Familiarity with generative AI tools is essential for this role. A strong foundation in big data analysis for extracting actionable business strategies is critical. Solid understanding of data governance and data quality principles is mandatory. Master of Science (M.Sc.) in Data Science or Master of Technology (M.Tech) in Artificial Intelligence/Data Science is required. Preferred certifications: Certified Data Scientist, Microsoft Certified: Azure Data Scientist Associate. Experience with agile and sprint management methodologies is beneficial. Proven ability to collaborate effectively with cross-functional teams.