Data Scientist / ML Engineer

📋 Description

• Architect, create, and sustain scalable data pipelines utilizing PySpark to effectively handle substantial data volumes.

• Design, validate, and enhance Machine Learning models for predictive analytics, incorporating regression, classification, and clustering methodologies.

• Oversee and implement Machine Learning environments and workflows via AWS SageMaker, while utilizing Athena for data querying and analysis.

• Embed Machine Learning models into production workflows, guaranteeing adequate monitoring, upkeep, and ongoing enhancement through MLOps best practices.

• Collaborate extensively with cross-functional teams to comprehend business challenges and convert them into data-driven solutions.

• Perform advanced data analysis utilizing Python and SQL to provide actionable insights.

• Work in a collaborative manner with multidisciplinary teams using Git/GitHub and agile development practices.

⛳️ Requirements

• 2–3 years of experience in Data Engineering, Machine Learning, or related fields.

• Advanced expertise in Python, including libraries such as Pandas, NumPy, and Scikit-learn.

• Strong SQL abilities for data querying, transformation, and analysis.

• Practical experience with PySpark for large-scale data handling.

• Comprehensive understanding of Machine Learning algorithms, including regression, classification, clustering, and hyperparameter optimization techniques.

• Experience with AWS services, particularly SageMaker and Athena.

• Familiarity with MLOps methodologies and experience in integrating and monitoring ML models in production settings.

• Proficiency with Git and collaborative development workflows utilizing GitHub.

• Strong analytical thinking and problem-solving capabilities.

• Curiosity, independence, attention to detail, and a collaborative attitude.

🏝️ Benefits

• 100% remote work

• Flexible hours

• Special timetable: Fridays and summer 7h.

• Individual budget for attending forums and training

• English classes

• Health insurance

• Every three years, 6 extra days off.

• Day off on your birthday

• Bring a friend and benefit from it

• Flexible compensation

• Wellness - Gympass

• Volunteering opportunities

• Company events and team buildings