Position Details
About this role
Data Science Senior Advisor bridges data science and engineering to productionize enterprise ML initiatives across multiple domains. The role develops, tests, and champions model lifecycle assets and collaborates with technical and business partners in a hybrid work arrangement.
Key Responsibilities
- Act as SME in MLOps frameworks, bridging data science and engineering
- Develop and productionalize enterprise ML initiatives
- Create model lifecycle assets for governance and reproducibility
- Collaborate with engineering and infrastructure teams
- Mentor data scientists and data engineers
Technical Overview
Stack includes Python, SQL, R, ML/DL frameworks (TensorFlow, PyTorch), Git, Databricks; emphasis on productionization, governance, and cross-domain collaboration.
Ideal Candidate
The ideal candidate is a mid-to-senior data scientist with 2+ years of data science experience, proficient in ML/DL frameworks (TensorFlow, PyTorch) and NLP. They excel at productionizing models, collaborating with engineers, and mentoring teammates in a hybrid New York setting.
Must-Have Skills
Tools & Platforms
Required Skills
Hard Skills
Soft Skills
Industry & Role
Keywords for Your Resume
Deal Breakers
No Master's degree in a quantitative field, Less than 2 years of data science experience, Lack of experience with Python, SQL, or ML frameworks
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