Title: Senior Lead Data Scientist Position Details
This is a high-level position designed for a visionary practitioner with 6 to 10 years of experience who can bridge the gap between advanced research and operational excellence. You will not only build sophisticated models but also architect end-to-end systems and mentor a growing team of data scientists.
Key Responsibilities
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ML Lifecycle Management: Oversee the full lifecycle from problem formulation and pipeline orchestration to model deployment and continuous monitoring.
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Production Excellence: Utilize Docker and Kubernetes to transition research prototypes into scalable high-performing production systems.
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Technical Leadership: Drive a culture of scientific rigor through code reviews mentorship and Agile management.
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Strategic Communication: Act as the primary bridge between technical teams and executive leadership translating complex findings into actionable business value.
Desired Qualifications
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Technical Stack: Expert-level Python/R mastery of deep learning frameworks (TensorFlow PyTorch) and big data tools (Spark SQL).
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Cloud Infrastructure: Hands-on experience with GCP SageMaker or Vertex AI.
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Education: A Masters degree or higher in a quantitative field (Statistics CS Physics etc.).
-
Preferred: Experience with Generative AI LLMs and RAG architectures.
Title: Senior Lead Data Scientist Position Details Location: Bay Area USA (Regular Shifts). Duration: Fulltime Role Overview This is a high-level position designed for a visionary practitioner with 6 to 10 years of experience who can bridge the gap between advanced research and operati...
Title: Senior Lead Data Scientist Position Details
This is a high-level position designed for a visionary practitioner with 6 to 10 years of experience who can bridge the gap between advanced research and operational excellence. You will not only build sophisticated models but also architect end-to-end systems and mentor a growing team of data scientists.
Key Responsibilities
-
ML Lifecycle Management: Oversee the full lifecycle from problem formulation and pipeline orchestration to model deployment and continuous monitoring.
-
Production Excellence: Utilize Docker and Kubernetes to transition research prototypes into scalable high-performing production systems.
-
Technical Leadership: Drive a culture of scientific rigor through code reviews mentorship and Agile management.
-
Strategic Communication: Act as the primary bridge between technical teams and executive leadership translating complex findings into actionable business value.
Desired Qualifications
-
Technical Stack: Expert-level Python/R mastery of deep learning frameworks (TensorFlow PyTorch) and big data tools (Spark SQL).
-
Cloud Infrastructure: Hands-on experience with GCP SageMaker or Vertex AI.
-
Education: A Masters degree or higher in a quantitative field (Statistics CS Physics etc.).
-
Preferred: Experience with Generative AI LLMs and RAG architectures.
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