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Data Scientist Architect
Résumé du poste
A tech company is looking for an Architect, Data Scientist for their Data & AI Team. You will be responsible for optimizing data ingestion and featurestore pipelines, prototyping and training models, and integrating AI-driven insights into applications. Candidates must have 10+ years of experience in data engineering, proficiency in Python and SQL, and strong skills in statistical modeling. This position allows for remote work in North America.
Qualifications
- 10+ years of experience in designing and deploying production-grade ML or data engineering solutions.
- Deep experience in enterprise platforms.
- Strong grounding in statistical modeling and ML evaluation metrics.
Responsabilités
- Architect and optimize data ingestion, ETL/ELT, and featurestore pipelines.
- Prototype, train, and evaluate predictive and generative models.
- Own CI/CD, monitoring, and scalable inference for ML and LLM pipelines.
Connaissances
Formation
Outils
A company is looking for an Architect, Data Scientist for their Data & AI Team (North America Remote).
- Architect and optimize data ingestion, ETL/ELT, and featurestore pipelines
- Prototype, train, and evaluate predictive and generative models while implementing experimentation pipelines
- Own CI/CD, monitoring, and scalable inference for ML and LLM pipelines, and integrate AI-driven insights into applications
- Bachelor's or Master's in Computer Science, Statistics, Math, or Data Science
- 10+ years of experience in designing and deploying production-grade ML or data engineering solutions
- Proficiency in Python and SQL, with deep experience in enterprise platforms like OpenSearch and Snowflake
- Strong grounding in statistical modeling and ML evaluation metrics
- Fluency with Linux, Git, CI/CD, Docker, and orchestration frameworks
* Le salaire de référence se base sur les salaires cibles des leaders du marché dans leurs secteurs correspondants. Il vise à servir de guide pour aider les membres Premium à évaluer les postes vacants et contribuer aux négociations salariales. Le salaire de référence n’est pas fourni directement par l’entreprise et peut pourrait être beaucoup plus élevé ou plus bas.
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