Senior Data Scientist – Artificial Intelligence

Keyrus

. Transform complex business challenges into scalable, modern, and results-driven data solutions .

Posted 10/2/2026full-timeRemote • BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying Data Science, Machine Learning, and Artificial Intelligence solutions, with a strong focus on Python programming, model lifecycle management, and collaboration with cross-functional teams. Proficient in transforming complex data challenges into scalable solutions while ensuring quality and performance.

Highest-signal resume keywords

Python ProgrammingMachine Learning Model DevelopmentGenerative AI SolutionsData Preparation and Feature EngineeringMLOps Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ScienceMachine LearningArtificial IntelligenceFeature EngineeringModel TrainingModel ValidationError AnalysisPerformance MeasurementStatistical AnalysisDeep Learning Frameworks

Soft Skills

Strong Communication SkillsCritical ThinkingCollaborationAutonomyCommitment to Continuous Learning

Tools & Technologies

PythonPandasNumPyScikit-learnGitSageMakerDatabricksAPIsCI/CD PracticesVector Databases

Industry Keywords

Data SolutionsModel LifecycleCloud-Based Data PlatformsLarge Language ModelsEmbeddingsRAGExperiment TrackingModel VersioningDeployment AutomationMonitoring

Tech Stack

Tools & technologies

NumpyPandasPythonScikit-Learn

About the role

Key responsibilities & impact

Transform complex business challenges into scalable, modern, and results-driven data solutions
Develop and evaluate statistical and Machine Learning models
Build Generative AI solutions using RAG, embeddings, vector search, and prompt engineering
Prepare data, perform feature engineering, and train and validate models
Take analytical or AI solutions from prototype to production
Ensure quality, monitoring, security, performance, cost efficiency, and governance throughout the model lifecycle
Work with structured and unstructured data
Collaborate with Product Managers, Architects, Engineers, Data Governance teams, and business subject-matter experts
Translate real-world needs into scalable and reliable solutions
Contribute to Keyrus Data Science, Machine Learning, and Artificial Intelligence projects

Requirements

What you’ll need

Bachelor's or postgraduate degree in Computer Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative field
More than 5 years of professional experience developing and deploying Data Science, Machine Learning, or Artificial Intelligence solutions
Strong knowledge of Python, including pandas, NumPy, scikit-learn, and relevant Deep Learning or Generative AI frameworks
Practical experience in data preparation, feature engineering, model training, validation, error analysis, and performance measurement
Experience taking analytical or AI solutions from prototype to production
Practical knowledge of Git, testing, code review, documentation, APIs, and CI/CD practices
Experience with cloud-based data and AI platforms, preferably SageMaker, Databricks, or equivalent technologies
Familiarity with MLOps practices, including experiment tracking, model versioning, deployment automation, and monitoring
Practical understanding of Large Language Models (LLMs), embeddings, vector databases, RAG, and the evaluation of GenAI solutions
Strong communication skills and the ability to collaborate with Product Managers, Architects, Engineers, Data Governance teams, and business subject-matter experts
Autonomy, critical thinking, and a commitment to continuous learning

Benefits

Comp & perks

Professional development opportunities in Data Science, Machine Learning, and Artificial Intelligence
Remote work
International and multicultural environment
Collaboration with teams across different specialties, functions, and geographies
Knowledge sharing and continuous improvement
Exposure to global projects and complex business challenges