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Build and maintain ETL pipelines, streaming data flows, and vector databases to power AI-driven marketing platforms using Databricks, Spark, and GCP.
Builds and maintains data pipelines and infrastructure to power AI/ML applications, collaborating with data scientists to integrate models into systems.
Senior data scientist builds and validates contextual bandit systems for retail e-commerce on AWS SageMaker, then takes 24/7 production ownership including monitoring, retraining, and A/B testing.
Builds data-driven solutions on AWS, engineering features and analytical workflows to turn datasets into business insights and scalable pipelines.
Builds data-driven solutions on AWS, engineering features and analytical workflows to turn datasets into insights and scalable pipelines.
Builds AWS-based data pipelines and analytical workflows, engineering features and turning large datasets into actionable insights for business decisions.
Builds AWS-based data pipelines and analytics solutions, engineering features and end-to-end workflows to turn raw data into business insights.
Develop, train, and integrate AI/ML models for government systems using Python, TensorFlow, and PyTorch, ensuring compliance with DoD cybersecurity and responsible AI policies.
Designs, builds, and deploys AI/ML models for industrial use cases like predictive maintenance and computer vision, using Python frameworks and cloud platforms.
Build predictive models and A/B tests in Python/SQL to guide pricing, inventory and marketing decisions for a global fashion retailer.
Build and deploy production-grade AI/ML services for Mastercard’s payments systems, collaborating with data scientists and engineers to ship reliable, scalable features.
Design and build a scalable data platform and analytics suite using Python/Scala, Spark, Hadoop, and cloud tools to power APIs and insights for customers.
Builds and maintains robust data pipelines using Python/Scala, Spark, Hadoop, and SQL to enable reliable data products and analytics workflows.
Lead a team building scalable data pipelines and feature stores to power AI model training and inference at Mastercard, ensuring high-quality, governed data for foundation models and downstream AI use cases.
Design and implement AI/ML frameworks to support business decision-making using Python or R, statistics, and model evaluation.
Build and deploy ML/AI models to extract insights and predict outcomes from large datasets using Python/R, then integrate them into business processes.
Build and maintain the data platform powering payments analytics and AI-driven features, including pipelines, storage, and self-serve tooling for analysts and product teams.
Design and build production-grade AI/ML platforms and MLOps pipelines for clients, using Python, cloud (GCP/AWS/Azure), Terraform, and tools like Vertex AI and Kubernetes.
Build and deploy AI/ML models for predictive maintenance using time-series sensor data to reduce equipment downtime in industrial and smart-infrastructure settings.
Build and maintain large-scale data pipelines and deep learning models to drive AI-driven insights for semiconductor and IoT solutions, using Python, TensorFlow/PyTorch, and cloud platforms.
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