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Tier-1 brand plus metro location and mid-senior role drive medium applicant competition.
Role demands deep Snowflake, ML/MLOps, and enterprise consulting experience, reducing cross-industry portability.
Explicit six-year minimum and mandatory ML, MLOps, cloud, and pre/post-sales skills create strict filters.
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Serve as a technical expert and strategic advisor for AI/ML data science workloads on the Snowflake Data Cloud.
Design and build AI/ML pipelines using Snowflake features and partner ecosystem tools based on customer requirements.
Collaborate with customers and System Integrators to ensure successful deployment, provide best practices, and deliver knowledge transfer enabling customer self-sufficiency.
University degree in data science, computer science, engineering, mathematics, or related field, or equivalent experience.
Minimum 6 years experience in pre-sales or post-sales technical customer-facing roles.
Hands-on experience with SQL and at least one programming language among Python, Java, or Scala, plus experience with data science libraries like Pandas, PyTorch, TensorFlow, or SciKit-Learn.
Experience with at least one public cloud platform (AWS, Azure, or GCP) and one Data Science tool such as AWS Sagemaker, AzureML, Dataiku, Datarobot, H2O, or Jupyter Notebooks.
Strong technical leadership in data science and AI/ML pipeline deployment in cloud environments.
Experience advising enterprises on Data Science lifecycle best practices, including MLOps and model management.
Ability to engage with both technical and executive stakeholders to drive strategic implementations and continuous product improvements.