Top Machine Learning Jobs in Mexico City

The Sr. Principal Data Scientist will assess data management within NSIC, develop data infrastructure guidelines, implement a data lifecycle management framework, ensure data quality, leverage advanced analytics techniques, and identify capacity building programs for personnel.

As a Sr. Data Scientist, you will lead the development of advanced scoring and indexing models for predicting business outcomes, collaborate with teams to integrate solutions, conduct data analysis, and ensure the accuracy of models while communicating insights to stakeholders.

As a Machine Learning Engineer at FanDuel, you will leverage data to enhance customer experiences and drive business insights. You will collaborate with engineering and data teams to manage data and develop AI-powered insights, turning user interactions into actionable knowledge.

The Business Intelligence Developer will design and implement BI solutions, create reports, dashboards, and visualizations from complex data. They will collaborate with stakeholders to understand data needs and enhance existing BI systems for accuracy and efficiency in data-driven decision-making.

As a Staff Data Engineer, you will lead the evolution of the CS Data Platform, building and maintaining data pipelines and APIs, collaborating with cross-functional teams to improve data handling capabilities for AI-driven customer support solutions.

As a Staff Machine Learning Data Scientist, you will lead the development of machine learning tools for patient data, integrating insights from diverse stakeholders, and conducting complex analyses in cloud environments. You'll collaborate with experts to provide innovative solutions and generate novel clinical insights from extensive patient data.

As a Data Scientist on the Growth team at Wave, you will design, run, and analyze experiments to enhance product features and customer experiences. The role involves working closely with operations and product teams to generate insights from data, applying statistical modeling and machine learning, and communicating findings to stakeholders.

Lead the design and development of robust data architectures that support scalable, secure, and efficient data pipelines. Drive innovation, mentor team members, ensure data quality and resilience, and collaborate with cross-functional teams to deliver impactful data solutions.