Manager, Data Science

Snowflake

Warsaw, Poland

We’re looking for a Data Science Manager to lead Snowflake's corporate machine learning function. In this role in the CIO’s org, you will be responsible for leading and managing a team of data/ML scientists who work on developing and integrating cutting-edge AI technologies – primarily Snowflake techstack – to meet our corporate internal needs. This role involves overseeing the strategy, development, and execution of data science initiatives, as well as ensuring the growth and professional development of the team.

AS A DATA SCIENCE MANAGER AT SNOWFLAKE, YOU WILL:

Lead and manage a team of data scientists, providing guidance and mentorship to ensure the success of the team;
Develop and execute data science strategies and initiatives that align with Snowflake's business goals;
Collaborate with cross-functional teams, including cloud engineering, sales, finance, and marketing, to ensure successful product development and launch;
Work closely with various stakeholders to understand their needs and incorporate feedback into data science initiatives;
Develop and execute data science strategies and initiatives that focus on LLM, NLP, as well as classical data science;
Stay abreast of the latest developments in AI technologies to ensure Snowflake remains a leader in this space.

OUR IDEAL CANDIDATE WILL HAVE:

Proven experience (2+ years) in data science management, ideally with a focus on AI, machine learning, and data engineering; total 10+ years’ experience in AI/ML;
Demonstrable experience productionalizing AI/ML projects;
Strong understanding of AI workflows and their applications in enterprise;
Excellent communication and leadership skills, with the ability to influence cross-functional teams with strong collaboration skills;
Ability to handle volatility and uncertainty in data science projects, with a focus on adapting to changing requirements and priorities;
Strong analytical skills, experience in leveraging data to make critical business decisions;
Knowledge and experience in cloud environments, such as AWS, Azure, and GCP;
Experience developing and deploying machine learning models for predictive analytics and forecasting;
Knowledge of natural language processing and text analytics, with a focus on sentiment analysis and topic modeling;
Strong GenAI/LLM fundamentals including in context learning, fine-tuning, inference, and language programming frameworks such as Langchain, and solid understanding of the transformer model.

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