Drive the innovation in data science by leading the design and implementation of sophisticated models and algorithms. This role leverages expertise in Python, PyTorch, and TensorFlow to tackle complex business challenges within the automotive domain.

The ideal candidate possesses advanced skills in data science, machine learning, and artificial intelligence, with a strong emphasis on deep learning frameworks.

A robust proficiency in Python is fundamental for algorithm implementation, model training, and successful deployment. Experience with Google Cloud Platform, including Vertex AI and BigQuery, is crucial for managing large datasets and utilizing cloud services effectively. Familiarity with containerization technologies like Docker is essential for establishing reproducible ML workflows. Strong collaboration skills are vital for working within cross-functional teams and promoting data-driven decision-making. Proficiency in version control systems is expected to streamline development processes.

- Lead the design and implementation of advanced data science models and algorithms. - Utilize Python, PyTorch, and TensorFlow to solve complex business problems. - Focus on deep learning frameworks and AI/ML advancements. - Manage large datasets and leverage cloud-based services on Google Cloud Platform. - Create reproducible ML workflows using containerization technologies like Docker. - Collaborate with cross-functional teams to drive data-driven decision-making. - Ensure streamlined development processes through proficiency in version control systems.

Possesses 6-10 years of experience in Data Science, with specific experience in the automotive domain.

A Master’s degree in Data Science or Machine Learning is required, complemented by a Bachelor’s degree in Computer Science with a specialization in AI or Data Science.

Proficiency in Python for algorithm implementation, model training, and deployment is essential.

Expertise in Google Cloud Platform, particularly Google Cloud Vertex AI and BigQuery, is required. Experience with containerization technologies like Docker is critical.

Candidates must demonstrate strong collaboration skills and proficiency with version control systems.

Certifications such as the TensorFlow Developer Certificate and Google Cloud Professional Data Engineer are considered advantageous. Experience with Google Cloud Dataflow and cloud data manipulation techniques is also beneficial.