Top Data Science Jobs in Mexico City

This internship offers hands-on experience in data analytics, focusing on advanced analytics and data modeling within various business units at CNA, including mentorship and potential full-time opportunities.

The Marketing Analyst will measure media investments, optimize marketing performance, support decision-making, and develop actionable insights through analysis and reporting.

The Data Owner Lead manages data quality, integrity, and governance, driving data solutions aligned with business objectives and fostering a data-driven culture.

The Director of Data Science & Analytics will manage a team, drive analytics vision, enhance product outcomes, and partner with executives.

The Manager, Data Science will lead a team of data scientists in developing machine learning models and data analysis to enhance banking experiences and security.

The role involves time-series forecasting, data analysis, enhancing forecasting processes, and consulting with stakeholders to optimize resource planning.

The Sr. Manager of Data Science and Analytics will oversee a team, guiding efforts in data analysis for payments and compliance, ensuring impactful outputs, and fostering team growth.

Manage a team of data analysts and scientists, focusing on analytics for payments and compliance. Ensure impactful data work and drive business decisions.

Manage a team of data analysts and scientists focused on Circle's payments products and compliance efforts, ensuring data quality, impactful reporting, and cross-functional collaboration.

Manage data analysts and data scientists for payments and compliance. Guide, improve team work, and collaborate with cross-functional partners.

The Data Scientist will design and implement machine learning algorithms, analyze datasets, communicate findings, and meet mission requirements using technical expertise.

Develop and implement advanced algorithms, apply statistical techniques, collaborate with clients, assess technologies, and mentor team members.

Manage pricing strategy for fantasy sports markets, lead a team, develop pricing models, collaborate cross-functionally, and ensure data integrity.

Lead the Product Analytics & Data Science team, focusing on mentorship, stakeholder management, and executing data projects to drive insights and value.

Lead a data science team to enhance patient acquisition and retention through data-driven insights and experimentation, while collaborating with various departments.

As a Data Science Platform Engineer, you will enhance predictive models, develop tools for real-time predictions, expand NLP capabilities, and ensure production system performance within a collaborative team.

The role involves leading a team to develop AI and ML solutions, manage customer interactions, and analyze large data sets using various technologies.

Develop advanced algorithms, apply statistical techniques, support clients with data analysis, contribute to emerging datasets, mentor junior associates, and advance thought leadership through research.

The Principal Consultant will lead data-driven consulting projects in the Technology, Media, and Entertainment sector, develop analytics frameworks, manage client relationships, and provide high-end analytics solutions to enhance marketing effectiveness and business strategies.

Agap Technologies Inc. offers online Data Science training, providing real-time instruction, interview training, and support for OPT applications with a professional environment.

Interns will engage in data science, engineering, and analytics roles, utilizing data to provide insights and improve decision-making processes for Chevron.

Lead a data science team, manage analytics strategies, collaborate with stakeholders, conduct complex data analyses, and drive business performance.

As a Data Scientist, you will build machine learning models and work with a cross-functional team to deliver impactful data-driven products.

The Manager, Data Science will lead a team to build machine learning models, leveraging various technologies to derive insights from large volumes of data while partnering across teams to achieve business goals.

Lead a cross-functional team to assess model risks, build machine learning models, and influence decision-making using advanced statistical techniques.