Senior Data Scientist

Avenga

. Design and implement scalable AI, Machine Learning, and Data Science architectures aligned with business and technical requirements .

Posted 11/12/2026full-timeMexicoSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing Artificial Intelligence and Machine Learning architectures, with a strong focus on model optimization, data quality assurance, and deployment in production environments. Proficient in leveraging advanced statistical techniques and collaborating with cross-functional teams to deliver scalable AI solutions.

Highest-signal resume keywords

Artificial Intelligence Architecture DesignMachine Learning Model DevelopmentPython DevelopmentTensorFlow and PyTorch ExperienceData Quality and Validation Mechanisms

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning AlgorithmsStatistical ModelingSQL Query OptimizationHyperparameter TuningLarge Language ModelsDocker DeploymentKubernetes DeploymentPrompt EngineeringCloudera ExperienceBig Data Processing

Soft Skills

Strong Communication SkillsCollaboration with Multidisciplinary Teams

Tools & Technologies

TensorFlowPyTorchKerasScikit-learnAWSAzureGoogle Cloud PlatformDockerKubernetesCloudera

Industry Keywords

Artificial IntelligenceMachine LearningData ScienceMLOpsPredictive AnalyticsReal-time Data ProcessingBatch Data ProcessingModel Lifecycle ManagementGenerative AIData Quality Assurance

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformKerasKubernetesPythonPyTorchScikit-LearnShell ScriptingSQLTensorflow

About the role

Key responsibilities & impact

Design and implement scalable AI, Machine Learning, and Data Science architectures aligned with business and technical requirements
Develop, train, validate, optimize, and deploy Machine Learning models into production environments
Build AI solutions leveraging traditional Machine Learning algorithms and Large Language Models
Define reliable data quality, validation, and control mechanisms to support AI initiatives
Optimize model performance through advanced statistical techniques and hyperparameter tuning
Support real-time and batch data processing scenarios across cloud and Big Data environments
Collaborate with engineering, data, and business stakeholders to translate complex challenges into production-ready AI solutions
Contribute to the continuous improvement and evolution of the organization's Artificial Intelligence capabilities

Requirements

What you’ll need

Strong experience designing and implementing Artificial Intelligence, Machine Learning, and Data Science architectures
Advanced knowledge of Machine Learning algorithms, including Decision Trees, Random Forest, SVM, K-Means, Naive Bayes, KNN, and Neural Networks
Strong hands-on development experience with Python and Shell Scripting
Experience with TensorFlow, PyTorch, Keras, and Scikit-learn
Hands-on experience with Large Language Models (LLMs) and Prompt Engineering
Strong knowledge of advanced statistical techniques, including statistical modeling, clustering, and predictive analytics
Experience developing and optimizing SQL queries
Experience defining data quality, control, validation, and assurance mechanisms
Experience deploying Machine Learning models into production environments using Docker and Kubernetes
Experience with Big Data and cloud ecosystems such as Cloudera, AWS, Azure, or GCP
Knowledge of real-time and batch data processing
Experience with advanced model optimization and hyperparameter tuning
Availability to work under a hybrid model, attending the office three days per week
Availability to travel when required by business or operational needs
Experience designing end-to-end AI solutions across complex or large-scale environments
Exposure to multiple cloud platforms, including AWS, Microsoft Azure, or Google Cloud Platform (GCP)
Experience integrating LLMs and Generative AI solutions into enterprise applications or business workflows
Knowledge of MLOps practices and model lifecycle management
Experience working with large-scale or distributed data environments such as Cloudera
Strong communication skills and experience collaborating with multidisciplinary technical and business teams

Benefits

Comp & perks

Equal opportunities regardless of race, ethnicity, gender identity, sexual orientation, disability, age, religion, or any other characteristic
Respectful and inclusive work environment
Hybrid work model