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Tier-1 brand, metro location, and broad mid-level ML/cloud skillset increase competition.
Snowflake-specific platform expertise and deep MLOps/data science focus limit cross-industry transferability.
Explicit 6+ years requirement plus mandatory ML, cloud, and scripting skills increases strictness.
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Serve as a technical expert on Snowflake for AI/ML/Data Science workloads, advising customers on best practices and strategic implementations.
Design and build ML pipelines using Snowflake features and partner ecosystem tools, including hands-on POCs with SQL and Python.
Collaborate with customer teams and System Integrators to ensure successful solution deployment and provide ongoing technical guidance.
Bachelor's degree in data science, computer science, engineering, mathematics or related field, or equivalent experience.
Minimum 6 years experience in customer-facing technical roles (pre-sales or post-sales).
Proficient in SQL and at least one programming language (Python, Java, or Scala).
Experience with at least one public cloud platform (AWS, Azure or GCP) and one Data Science tool (e.g., AWS SageMaker, AzureML, Dataiku).
Deep understanding of Data Science lifecycle including feature engineering, model development, deployment, and management with MLOps expertise.
Effective communicator capable of presenting complex technical concepts to both technical and executive audiences.
Experience working closely with Systems Integrators and in enterprise software deployments, preferably with exposure to Generative AI, LLMs, or Vector Databases.