You will design, build, and deploy data-driven solutions leveraging large-scale datasets, machine learning, and generative AI.
Responsibilities
- Develop, validate, and deploy machine learning and statistical models for prediction, classification, and optimization.
- Design and maintain end-to-end data science pipelines, from ingestion through model deployment and monitoring.
- Design and integrate Microsoft Copilot-based solutions and develop prompt engineering strategies.
- Build and deploy models using cloud-native services across Azure (e.g., Azure ML, Synapse Analytics) or AWS (e.g., SageMaker).
- Translate complex business requirements into scalable, cloud-native analytics and AI solutions while ensuring responsible AI practices.
Required Skills
- 5+ years of experience in data science, machine learning, or applied analytics.
- Strong proficiency in Python and SQL, with experience working with large-scale datasets.
- Hands-on experience with Microsoft Copilot or Azure AI services, or AWS ML/analytics tools.
- Solid understanding of machine learning algorithms and statistical modeling.
- Experience deploying models in production cloud environments (MLOps).
- Proficiency in Data Visualization and Business Communication.
- Experience with Cloud Computing platforms (Azure or AWS).