lead advanced analytics, machine learning, and generative AI initiatives across the full life cycle from data exploration to production deployment.
apply modern MLOps practices (automated pipelines, CI/CD for ML, scalable model serving, monitoring) and integrates models into production via APIs and microservices.
Manage and develop a team of data scientists, guiding their work, and setting technical quality standards.
Collaborate with engineering and product teams is essential, alongside translating analytical outcomes into clear, actionable recommendations that influence strategic decisions.
Requirements:
3-5 Years of experience.
strong experience with lakehouse architectures (e.g., Delta Lake, Iceberg, Spark) and participation in Data Mesh/Data Grid environments to deliver robust, domain-oriented data products, in addition to driving GenAI experimentation and fine-tuning.
