Data Scientist, Mid-level

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November 12

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Leega

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API • Artificial Intelligence • Cloud Solutions

Leega is a leading technology solutions provider in Latin America, specializing in data analytics and cloud solutions. As the first company in the region certified by Google Cloud for Data Analytics, Leega offers a range of services including application development, machine learning, and risk management analytics. The firm partners with major cloud services such as AWS and Microsoft Azure to help businesses enhance their data management and transition effectively to the cloud, ultimately driving digital transformation and innovation.

201 - 500 employees

Founded 2010

🔌 API

🤖 Artificial Intelligence

📋 Description

• Understand business needs and ML/AI requirements: Collaborate with stakeholders and Senior Data Scientists to understand business problems and translate them into testable hypotheses and machine learning projects. • Participate in data- and AI-driven discussions: Contribute initial analyses, insights, and model proposals to address data and AI challenges. • Act as an interface between Technology and Data Science teams: Work closely with Data Engineers and Architects to ensure data availability and efficient model training. • Clean, transform, standardize, and enrich raw data using the processing power of Azure Databricks and Spark. • Conduct Exploratory Data Analysis (EDA) to understand distributions, identify outliers, and select relevant features (feature engineering). • Build, train, and validate predictive models (regression, classification, clustering) using data science frameworks such as Scikit-Learn, TensorFlow, or PyTorch. • Document and present model results and performance metrics (e.g., AUC, F1 score). • Assist in transitioning developed models to production environments, using tools like MLflow for experiment and model tracking and management in Azure Databricks. • Monitor data and model quality: track data quality, integrity and drift, and model performance in production, proposing adjustments when necessary.

🎯 Requirements

• Experience with CI/CD tools and automation for machine learning workflows. • Data observability. • Familiarity with data monitoring and validation tools. • Pipeline orchestration. • Proficiency in SQL. • Data lakes and data warehouses. • Ability to manage data lakes for AI data preparation, with a focus on Azure Databricks. • Feature storage. • Cloud: Azure + Databricks. • Ability to collaborate with other Data Scientists to prepare datasets for AI models, ensuring high quality and performance. • Implementation of automated pipelines for model training, validation, deployment, and monitoring. • Ability to define and manage feature repositories for AI models (feature engineering). • Knowledge of LGPD/GDPR to ensure regulatory compliance in the processing of data for AI. • Experience working with agile methodologies (Scrum/Kanban). • Ability to understand business requirements and convert them into technical AI solutions.

🏖️ Benefits

• 🏥 Porto Seguro Health Plan • 🦷 Porto Seguro Dental Plan • 💰 Profit Sharing (PLR) • 👶 Childcare Assistance • 🍽️ Alelo Meal and Food Vouchers • 💻 Home Office Allowance • 📚 Partnerships with Educational Institutions • 🚀 Support for Certifications, including Cloud • 🎁 Livelo Points • 🏋️‍♂️ TotalPass • 🧘‍♂️ Mindself