Top Machine Learning Jobs in Mexico City

Seeking experienced Quantitative Analyst to develop models, analyze data, and support investment decisions in collaboration with portfolio managers.

The Senior Associate, Private Market Valuation will perform valuations for alternative investments, enhance financial models, and build client relationships while using advanced techniques like AI and machine learning to improve efficiency and accuracy.

The Senior Associate will deliver valuation services for alternative investments, handle cash-flow models, collaborate with teams, and enhance valuation tools using technology.

The Associate Director leads data management and portfolio analytics initiatives, transforming data into insights for better business decisions and patient outcomes, while managing a team and driving innovation.

Lead AI & ML projects, engage with stakeholders, provide technical leadership, mentor junior scientists, develop end-to-end ML solutions, and showcase customer solutions.

As an AI Scientist at WorldQuant, you'll conduct machine learning research, produce trading signals, collaborate with portfolio managers, and develop predictive models.

TigerGraph seeks individuals to promote their scalable graph database technology used for analytics and machine learning across various industries.

The Staff Data Scientist/Machine Learning Engineer will develop ML systems to engage retailers, mentor senior data scientists, and optimize marketing strategies using data insights.

The Strategy & Analytics Lead will drive product decisions through data-driven insights, collaborating with cross-functional teams to enhance business growth.

Lead data partnerships by executing data acquisition strategies, negotiating agreements, and evaluating data quality in clinical and observational studies.

As a Financial Engineer, design and maintain advanced financial models while providing analytical support for trading and hedging activities. Collaborate with stakeholders to enhance operational efficiency through advanced analytics and automation.

Assist in quantitative research and development, focusing on high-frequency trading, statistical arbitrage, and market-making strategies. Rotate through various tracks during the internship.

Develop and productionize a next-gen Dispatch System, build predictive models, automate processes, and lead a small team in optimizing operations.

Lead the technical vision for machine learning in search and recommendation systems, ensuring effective implementation and high standards. Collaborate across teams, balance research with practical applications, and simplify complex problems.

The VP of Data Science will lead Read AI's technical foundation in AI and ML, overseeing a team focused on building and scaling AI models and infrastructure.

The Technical Lead Bioinformatics Scientist will analyze complex sensor data for clinical initiatives, mentor staff, and develop databases for data organization.

As a Staff Analytics Engineer, you'll build production data workflows, ensure data integrity, and create customer-facing data insight products using SQL and Python.

The Integrated Insights Leader will drive strategic insights for Roche's pharma products, collaborating with R&D and commercial teams to enhance patient outcomes and market success through data analysis and customer-centric strategies.

As a Graduate Quantitative Researcher, you will develop algorithmic trading strategies using statistical models and machine learning, while collaborating with a research team.

As a Quantitative Research Intern, you'll work on research projects involving statistical models and machine learning to improve trading algorithms and strategies, impacting real-world trading decisions.

Develop and implement algorithmic trading strategies using statistical models and machine learning, analyzing large data sets to predict market movements.

As a Quantitative Research Intern, you'll develop trading algorithms and analyze strategies using statistics and machine learning, impacting Optiver's trading decisions.

As a Graduate Quantitative Researcher, you will develop algorithmic trading strategies using statistical models and machine learning while working with big data technologies.

Develop and implement algorithmic trading strategies using statistical models and machine learning to analyze and predict market movements while collaborating in a research team.

The Principal Data Scientist will develop algorithms, drive machine learning roadmap, collaborate with teams, and improve rider experiences through predictive models.