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SoTalent · Mexico City Metropolitan Area

Data Scientist

Hybridseniorfull timePosted yesterday
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Data Scientist III

📍 Location:Ciudad de México, Mexico (Remote | Hybrid)

🏢 Industry: Technology, Information and Media

💼 Work Setting: (Continental U.S.) with occasional travel.

Are you passionate about leveraging Artificial Intelligence and Data Science to solve complex scientific challenges and accelerate innovation? We are seeking an AI/Data Scientist to design, develop, and deploy advanced machine learning, natural language processing, and generative AI solutions that unlock insights from large-scale datasets. This role offers the opportunity to work at the forefront of AI innovation, building production-ready systems that enhance knowledge discovery, decision-making, and research outcomes.

Key Responsibilities

AI & Machine Learning Development

- Design, develop, and deploy machine learning and AI solutions that address complex scientific and business challenges.

- Build predictive, classification, and recommendation models using structured and unstructured data sources.

- Develop and optimize advanced machine learning algorithms for large-scale data environments.

- Evaluate model performance and continuously improve accuracy, reliability, and scalability.

Natural Language Processing & Generative AI

- Design and implement Natural Language Processing (NLP) solutions for knowledge extraction, content analysis, and information retrieval.

- Develop applications powered by Large Language Models (LLMs) and generative AI technologies.

- Build intelligent systems that transform large volumes of unstructured information into actionable insights.

- Fine-tune, evaluate, and optimize AI models to enhance performance and user experiences.

Data Science & Analytics

- Analyze large and complex datasets to uncover patterns, trends, and opportunities.

- Apply statistical modeling, data mining, and analytical techniques to solve real-world problems.

- Develop data pipelines and workflows to support AI model development and deployment.

- Ensure data quality, governance, and integrity throughout the AI lifecycle.

Cross-Functional Collaboration

- Partner with researchers, engineers, product teams, and business stakeholders to identify AI opportunities and define solution requirements.

- Translate business and scientific objectives into scalable technical solutions.

- Support end-to-end AI project delivery from concept and experimentation through production deployment.

- Communicate findings, recommendations, and technical concepts to both technical and non-technical audiences.

Production AI & Innovation

- Build production-ready AI systems with a focus on scalability, performance, reliability, and maintainability.

- Monitor deployed models and implement improvements based on usage and performance metrics.

- Research emerging AI technologies and evaluate their applicability to business and scientific use cases.

- Contribute to AI best practices, governance standards, and innovation initiatives.

Required Qualifications

- Bachelor's, Master's, or PhD in Computer Science, Data Science, Applied Mathematics, Statistics, Artificial Intelligence, Engineering, or a related quantitative discipline.

- Proven experience in Data Science, Machine Learning, and Artificial Intelligence development.

- Strong proficiency in Python for data analysis, model development, and deployment.

- Experience developing and implementing Natural Language Processing (NLP) solutions.

- Hands-on experience with Generative AI and Large Language Models (LLMs).

- Experience working with large-scale structured and unstructured datasets.

- Strong understanding of statistical analysis, machine learning methodologies, and model evaluation techniques.

- Ability to develop production-quality AI solutions and deploy models into operational environments.

- Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

- Experience with deep learning frameworks and modern AI development platforms.

- Knowledge of information retrieval, semantic search, and knowledge extraction techniques.

- Familiarity with cloud-based AI and machine learning services.

- Experience optimizing AI systems for scalability, efficiency, and reliability.

- Understanding of MLOps practices, model monitoring, and deployment automation.

- Experience collaborating within research-intensive or data-driven environments.

Key Skills

- Artificial Intelligence (AI)

- Machine Learning

- Natural Language Processing (NLP)

- Generative AI

- Large Language Models (LLMs)

- Data Science

- Python

- Statistical Analysis

- Applied Mathematics

- Deep Learning

- Data Mining

- Predictive Modeling

- Content Analysis

- Information Retrieval

- Large-Scale Data Processing

- Model Evaluation & Optimization

- Data Engineering

- AI Solution Development

- Research & Innovation

- Cross-Functional Collaboration

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