- Expertise in Data Science & AI/ML: 6-8 years' experience designing, developing, and deploying scalable AI/ML solutions for Big Data, with proficiency in Python, SQL, TensorFlow, PyTorch, Scikit-learn, and Big Data ML libraries (e.g., Spark MLlib).
- Cloud Proficiency: Proven experience with cloud-based Big Data services (GCP preferred, AWS/Azure a plus) for AI/ML model deployment and Big Data pipelines.; understanding of data modeling, warehousing, and ETL in Big Data contexts.
- Analytical & Communication Skills: Ability to extract actionable insights from large datasets, apply statistical methods, and effectively communicate complex findings to both technical and non-technical audiences (visualization skills a plus).
Educational Background: Bachelor's or Master's degree in a quantitative field (Computer Science, Data Science, Engineering, Statistics, Mathematics)