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Oversee data science projects and monitor results from one place.
Ensure scalability with environment and cluster management features.
Own the modeling process from exploratory analysis to deployment.
Forecast risk with machine learning techniques and use the results to inform pricing.
Develop strategies to make more profitable loans and approve credit applications.
Analyze clinical research, create more effective drugs, and assess drug safety.
Plan feature improvements according to trends in customer interaction data.
Build models to predict equipment maintenance and monitor performance.
"I love that my data scientists can spin up their own instances and deploy models as APIs. It saves us so much time."
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