Alexis O.
Director Of Clinical Data Science Specializing In Data Management
Role: data-scientist
Location: mexico
Level: director
48 pre-vetted professionals available
Director Of Clinical Data Science Specializing In Data Management
Role: data-scientist
Location: mexico
Level: director
Manager Data Scientist Specializing In Risk Modeling
Role: data-scientist
Location: mexico
Level: lead
Data Science Manager With Expertise In Analytical Modeling
Role: data-scientist
Location: mexico
Level: lead
Data Science Manager Specializing In Python Technologies
Role: data-scientist
Location: mexico
Level: lead
Data Science Manager With Expertise In Business Analytics
Role: data-scientist
Location: mexico
Level: lead
Data Science Manager Specializing In Statistical Analysis
Role: data-scientist
Location: mexico
Level: lead
English proficiency in LATAM has been rising steadily, especially among tech professionals. Argentina ranks in the High proficiency band (highest in LATAM), and engineers often speak near-native English. Other countries like Uruguay and Chile also have many fluent English speakers in tech. Mexico and Brazil are generally in the Moderate proficiency range, but in tech hubs you'll find large communities of developers comfortable with English due to multinational company presence and university requirements. Colombia and Peru historically scored lower on English, but younger generations of engineers have improved their skills and can communicate effectively. It's common for LATAM tech workers to have practical English for reading documentation, writing code, and having technical discussions.
Yes—one of the biggest advantages of LATAM talent is the time zone alignment with U.S. and Canadian business hours. The majority of LATAM countries fall within 1–3 hours of U.S. Eastern Time. Mexico spans Pacific to Central time zones, Andean countries like Colombia and Peru are on Eastern Time with no or minimal difference, and Southern Cone countries (Argentina, Brazil, Chile) are slightly ahead but still close to EST. This means developers in LATAM can easily join daily stand-ups, real-time meetings, and collaborate during the U.S. workday. In practice, LATAM engineers typically adjust to their client's schedule, significantly reducing project friction.
Mexico combines proximity and depth of talent. Its close geographic and time zone alignment with the U.S. facilitates tight coordination during AI/ML projects, while a massive STEM education pipeline (over 110,000 new engineers annually) supplies specialists in data science, machine learning, and cloud. Many Mexican ML engineers have experience in applied AI through the country's strong fintech and e-commerce sectors. Mexico's blend of U.S.-caliber skills, English fluency, and lower costs makes it a top choice for building data and AI teams.
The cost of hiring a data scientist in LATAM is typically 30–50% lower than in the U.S. or Western Europe. On average, a mid-level data scientist might command around $40–$70 USD per hour in Latin America, whereas in the U.S. the same might be $100+ per hour. Costs vary by country and experience: Argentina and Chile have slightly higher rates (senior data scientists ~$60–85/hr), while Colombia or Peru might be on the lower end (senior ~$40–60/hr). Many LATAM data scientists have excellent math and engineering backgrounds, so you're paying less not due to lower quality, but due to lower prevailing wages in their home country.
LATAM offers a sweet spot for AI/ML talent in terms of cost, quality, and convenience. Engineers cost 30–50% less than U.S. equivalents while delivering comparable skill levels. The time zone alignment means developers can join stand-ups, collaborate in real time, and respond same-day—advantages that Asia or Europe can't match for U.S. teams. Cultural compatibility, growing startup ecosystems, and government investment in STEM education all contribute to a deep, accessible talent pool. Top LATAM tech hubs (Mexico City, São Paulo, Buenos Aires, Medellín) rival any global city for AI/ML expertise.