Job Description

Overview:

Job Purpose

 

We are seeking a highly skilled and experienced Data Scientist to join our Data Warehouse & Analytics team. The ideal candidate will have a strong background in Snowflake, Python, machine learning, and AI to drive data-driven decision-making and predictive analytics. This role provides a unique opportunity to work with large-scale data on peta-bytes and make significant contributions to ICE. 

 

Responsibilities

• Develop and implement advanced analytics models using machine learning and AI techniques.
• Collaborate with cross-functional teams to understand business needs and provide data-driven solutions.
• Design and maintain scalable and robust data pipelines in Snowflake.
• Analyzing data and sharing meaningful insights
• Write clean, efficient, and well-documented Python code to perform data analysis and modeling.
• Stay up to date with the latest technologies and trends in data science and machine learning.

Knowledge and Experience

• Bachelor’s or Master's in Computer Science, Analytics, Statistics, Mathematics, or a related field.
• Minimum of 3 years of experience in a data science role, with a focus on Snowflake, Python, SQL, Machine Learning, and AI.
• Minimum of 3 years of experience in Tableau or any other data visualization tool
• Proven track record of developing and deploying machine learning models in a production environment.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities.

Preferred

• Experience with cloud platforms and services.
• Knowledge of additional programming languages and frameworks is a plus.

Intercontinental Exchange, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to legally protected characteristics.  

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----------: Intercontinental Exchange, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to legally protected characteristics.

Job Tags

Full time,

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