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Senior specialized role but metro location and broad skill requirements increase applicant density.
Role requires deep ML/AI and data architecture skills, making cross-industry transferability limited.
Explicit 13+ years requirement plus mandatory ML, data engineering, and cloud expertise makes filters strict.
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Design and architect end-to-end scalable data science and AI solutions aligned with business objectives.
Provide technical leadership and mentorship to data science teams, ensuring best practices in data modeling, infrastructure, and deployment.
Oversee integration, deployment, data governance, and performance monitoring of data architectures on cloud platforms such as AWS and Azure.
Bachelor's degree with 13+ years relevant experience or equivalent combination of education and experience; Master's degree preferred.
Proficiency in data science methodologies, programming languages (Python, R, Scala), and machine learning.
Experience with data engineering, ETL, big data technologies (Hadoop, Spark, Kafka), and cloud platforms (AWS, Azure, Google Cloud).
Strong knowledge in data architecture, software development practices (Git, Docker, Kubernetes), and data governance/compliance.
Senior-level data science professional with extensive experience architecting scalable AI and data solutions in large enterprises.
Technical leader capable of managing end-to-end data infrastructure design, team guidance, and stakeholder communication.
Experienced in cloud-based data architectures and integration, with proficiency in both data science and data engineering disciplines.