Senior Data Scientist

Vertem

. Develop, train, and validate machine learning models applied to real-world business problems .

Posted 10/3/2026full-timeBarueri • BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing, training, and deploying machine learning models using Databricks and Python, with a strong focus on feature engineering and data preparation. Proficient in monitoring model performance and collaborating with cross-functional teams to enhance data-driven solutions.

Highest-signal resume keywords

Databricks ExperienceMachine Learning Model DeploymentFeature EngineeringPython ProficiencyAutoML Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Supervised Machine LearningUnsupervised Machine LearningModel ScoringData PreparationScikit-LearnXGBoostLightGBMData Lake ExperienceBig Data EnvironmentsMLflow Experience

Tools & Technologies

Databricks EcosystemAWS Data LakeDatabricks AutoML

Industry Keywords

Machine LearningModel MonitoringAdvanced AnalyticsData ProductsRecommendation Modeling

Tech Stack

Tools & technologies

AWSPythonScikit-Learn

About the role

Key responsibilities & impact

Develop, train, and validate machine learning models applied to real-world business problems
Work with large volumes of data stored in the corporate AWS Data Lake
Use the Databricks ecosystem for model experimentation, training, and operationalization
Build data pipelines and model training pipelines
Use Databricks AutoML capabilities to accelerate experimentation and model generation
Perform feature engineering and data preparation for analytical models
Implement and maintain machine learning model deployment and scoring processes in production
Monitor model performance, assessing degradation and the need for retraining
Collaborate with data engineering, BI, and data product teams
Support the evolution of the company’s intelligence platform

Requirements

What you’ll need

Experience with Databricks
Experience developing supervised and unsupervised machine learning models
Knowledge of AutoML in Databricks
Experience deploying machine learning models to production
Knowledge of model scoring and inference pipelines
Experience with feature engineering and data preparation for analytical models
Proficiency in Python applied to data science
Experience with scikit-learn, XGBoost, and LightGBM
Experience working with data in Data Lake and Big Data environments
Preferred: experience with MLflow
Preferred: experience with machine learning model monitoring and governance
Preferred: experience with recommendation, segmentation, or propensity modeling projects
Preferred: experience with AWS data environments
Preferred: experience with advanced analytics projects and data products

Benefits

Comp & perks

Flexible Office – 2 days working from home and 3 days onsite
Birthday day off
Flexible working hours
SulAmérica health and dental insurance
SulAmérica life insurance
Psychological support
On-site massage
Relaxation room
TotalPass – Access to gyms and physical activities
Flexible meal or food allowance – BRL 41.91 per day
Childcare allowance – For children up to 5 years old
Transportation allowance, parking, or company shuttle
Qulture.Rocks – Performance and development management platform
Education allowance – Available after 12 months with the company
Inspiring and disruptive culture
Newborn kit
Internal events and engagement initiatives
Exclusive benefits on commemorative dates