Senior Data Scientist, Machine Learning, AI

Compass

. Develop predictive models and Machine Learning solutions for complex business problems, from data exploration through model validation, interpretation, and deployment .

Posted 9/23/2026full-timeGuarulhos • BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying Machine Learning models and solutions using Python, with a strong focus on data processing and analytics in AWS environments. Proficient in optimizing data pipelines and applying best practices for model lifecycle management.

Highest-signal resume keywords

Machine Learning Solutions DevelopmentPython Programming for Data ScienceAWS Services (SageMaker, Glue, EMR, Athena, Redshift)Apache Spark/PySpark for Data ProcessingPredictive Modeling and Data Analysis

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningPredictive ModelingPythonDeep LearningScikit-learnXGBoostApache SparkSQLTensorFlowData Pipeline Optimization

Soft Skills

Analytical SkillsProblem-SolvingCollaborationCommunicationResilience

Tools & Technologies

JupyterDatabricksMLflowApache KafkaAmazon Kinesis

Industry Keywords

Data ScienceMachine LearningArtificial IntelligenceAgile/ScrumETL Tools

Tech Stack

Tools & technologies

Amazon RedshiftApacheAWSETLInformaticaKafkaNoSQLPySparkPythonPyTorchScikit-LearnSparkSQLTensorflow

About the role

Key responsibilities & impact

Develop predictive models and Machine Learning solutions for complex business problems, from data exploration through model validation, interpretation, and deployment
Translate business needs into analytical questions, technical requirements, datasets, and Data and Machine Learning solutions
Develop Python solutions using supervised learning, unsupervised learning, and Deep Learning techniques
Participate in the design and technical definition of new Data, Machine Learning, and Artificial Intelligence solutions and features
Develop, enhance, and optimize data pipelines and platforms for large-scale processing using Spark/PySpark, Kafka, and/or Amazon Kinesis
Work with AWS Data, Analytics, and Machine Learning services such as SageMaker, Glue, EMR, Athena, Redshift, and Lake Formation
Implement, optimize, monitor, and support models, pipelines, and production features, ensuring performance, scalability, stability, and reliability
Explore data and model results, identifying patterns, opportunities, and improvements for the business
Apply best practices for experimentation, testing, version control, and lifecycle management of models and pipelines
Collaborate with Engineering, Data, Product, and Business teams to build end-to-end solutions
Solve problems and manage technical dependencies in dynamic, highly complex environments

Requirements

What you’ll need

Availability to work in a hybrid arrangement two days per week at R. Carlo Bauduco, 200—Vila Paraíso, Guarulhos, São Paulo
Professional experience as a Data Scientist, with hands-on Machine Learning experience
Hands-on experience with Python applied to Data Science and Machine Learning
Experience developing predictive models for real-world business problems
Knowledge of supervised learning, unsupervised learning, and Deep Learning
Experience with Scikit-learn, XGBoost, and/or LightGBM
Knowledge of Statsmodels and/or SciPy
Experience with Jupyter and/or Databricks
Knowledge of MLflow and best practices for experimentation and model lifecycle management
Experience with AWS for Data, Analytics, and Machine Learning, especially Amazon SageMaker, as well as Glue, EMR, Athena, and Redshift
Experience with large-scale data processing using Apache Spark/PySpark
Experience with Apache Kafka and/or Amazon Kinesis, including streaming data processing
Knowledge of designing, developing, and optimizing data pipelines and platforms
Knowledge of SQL, Git, distributed processing, performance, and scalability
Knowledge of NLP and/or Computer Vision
Experience with or knowledge of TensorFlow, PyTorch, and/or Apache Flink
Knowledge of Delta Lake/Delta Tables, AWS Lake Formation, and/or NoSQL technologies is a plus
Knowledge of ETL tools such as Informatica PowerCenter, data modeling/PowerDesigner, and Power BI is a plus
Strong logical reasoning, analytical, problem-solving, communication, collaboration, resilience, and dependency management skills
Knowledge of or experience with Agile/Scrum methodologies

Benefits

Comp & perks

This position is also open to candidates with disabilities
Hybrid work arrangement two days per week