Develop and deploy Machine Learning models for predictive analytics, classification, clustering, NLP or computer vision applications
Design, develop and maintain cloud-based ETL (Extract, Transform, Load) workflows to support AI and analytics pipelines
Build and optimize data lakes, data warehouses, and real-time data processing systems using cloud services such as AWS Redshift, Azure Synapse or Google BigQuery
Deploy ML models using MLOps best practices, ensuring scalability and automation in cloud environments.
Extract and transform data from various sources, ensuring data integrity and consistency.
Run and optimize existing data models, identifying opportunities for enhancements.
Modify, update, and maintain data pipelines and workflows as per business requirements.
Collaborate with data analysts and business stakeholders to support reporting and analytics needs
Tools and skills:
Masters or Bachelors degree in data science, Computer Engineering, Math, Statistics, Economics or related analytics field from top-tier universities with strong record of achievement
4+ years experience with solid analytical skills and an entrepreneurial, hands-on approach
Hands-on experience with at least one major cloud provider: