Principal Machine Learning Scientist
3 weeks ago
Snowflake is seeking a highly skilled Principal Machine Learning Scientist to lead our corporate machine learning function. As a key member of our team, you will apply AI and ML to a variety of domain-specific problems across Snowflake's business data.
Key Responsibilities- Lead projects: Conceptualize, design, and execute large ML projects, aligning with business goals, delivering measurable value, and impact.
- Engage with stakeholders: Lead conversations with technical and non-technical stakeholders, identify areas where AI and ML can be applied, and facilitate discussions around key drivers for decision-making and operational efficiencies.
- Provide technical and thought leadership: Design and implement advanced machine learning techniques, focusing on robust and scalable solutions.
- Provide mentorship: Mentor junior ML and Data Scientists on problem formulation, technical design, algorithm choices, and code quality.
- Develop hands-on: Analyze large amounts of data, manage data quality, design and develop complex ML models, deploy and manage production-grade applications end-to-end, and tell the story in a compelling manner.
- Partner with customers: Showcase internal solutions to customers, help them envision solutions stringing Snowflake platform capabilities together, and partner with internal teams that enable customer solutions.
- High levels of curiosity, eager enthusiasm, and demonstrable experience working on open-ended problems.
- Exceptional problem-solving skills with the ability to think strategically.
- Demonstrable experience and interest in problem formulation based on relatively abstract information.
- High levels of adaptability, to respond to fast-evolving project scope, adjusting strategies and plans accordingly.
- 7+ years of experience applying machine learning or statistical modeling on large datasets.
- Deep understanding of the basic classes of ML algorithms, statistics, and linear algebra.
- Technical expertise in one or more of the following topics: Anomaly Detection, Clustering, Time-Series Analysis and Forecasting, Natural Language Processing (NLP), Uncertainty Quantification.
- Experience building LLM-based applications in a business environment.
- Expert software development lifecycle and best practices.
- Domain knowledge and experience in the application of ML to one of Corporate Sales, Sales Engineering, Security, and Econometrics.
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