Requirements
- Minimum 3 years of professional experience in Data Science, Machine Learning Engineering, or Application Development involving data integration
- Can speak English is a must
- Expert proficiency in Python and its scientific libraries (e.g., Pandas, NumPy, Scikit-learn, TensoFlowPyTorch).
- Hands-on experience working with at least one major cloud platform, preferably AWS or Azure, including understanding of their data and compute services
- Solid understanding of software development principles, version control (Git), and model deployment/monitoring best practices.
Job Description
- Design, develop, and implement machine learning and statistical models tailored for innovative application features
- Work closely with application development teamns to integrate models and data-driven features into production systems.
- Write clean, efficient, and scalable code primarily using Python for model training, deployment, and automation.
- Utilize and manage cloud resources on AWS and/or Azure for data storage, processing, and model deployment (e.g., using services like SageMaker, Azure ML, or cloud-based data warehouses).
- Rapidly prototype and develop end-to-end data products and proof-of-concepts (POCs) that solve emerging business challenges.
- Communicate complex methodologies and results effectively to both technical and non-technical stakeholders.