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Data Science Scientist - Remote
Online/Remoto - Ideal para candidatos en
México
Publicado en 2026-01-16
México
Empresa:
Turing
Remoto/Desde casa
posición Publicado en 2026-01-16
Especializaciones laborales:
-
TI/Tecnología
Ingeniero de IA, Machine Learning
Descripción del trabajo
We’re looking for a Data Scientist who has excellent hands on Python skills and Machine Learning experience — someone who lives and breathes code, optimizes for performance, and has proven mastery on competitive programming or data challenge platforms like Leet Code, Code forces, Hacker Rank, or Kaggle . In this role you will be working with Turing team members and AI researchers at Frontier Labs to devise techniques and build data sets to improve performance of models.
Build, test, and optimize high-performance Python systems used in large-scale AI and data pipelines.
Design and maintain modular, clean, and production-ready Python codebases.
Collaborate with cross-functional teams (data, infra, and research engineers) to deliver reliable backend components.
Write efficient, maintainable, and testable code with strong focus on algorithms and data structures .
Stay current with modern Python tools, frameworks, ML advancements and best practices.
Bachelor’s or Master’s in Computer Science, Software Engineering, or a related field.
~4+ years of professional experience writing Python in production environments.
~ Expert-level proficiency in Python and core libraries (Pandas, Num Py, Async
IO, Pytorch, Transformers, or similar).
~ Proven track record on coding platforms — e.g.,
Experience with system design, clean architecture, and performance optimization.
~ Working level Proficiency in either Machine Learning or Data Science for Machine Learning.
Recognized performance in Kaggle , Code forces , or ICPC/Top Coder contests.
Deep curiosity for performance tuning, scalability, and elegant code design.
Perks of Freelancing with Turing:
Work fully remotely, from anywhere.
Type: Contractor (no medical/paid leave).
Technical Interview (60 mins): discussion of Python problem-solving, architecture, and system design.
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