Austin, TX 73301 (St Edwards area)
Job detailsJob TypeFull-timeFull Job DescriptionIntroduction
As a Data Scientist at IBM, you will help transform our clients data into tangible business value by analyzing information, communicating outcomes and collaborating on product development.
Work with Best in Class open source and visual tools, along with the most flexible and scalable deployment options.
Whether its investigating patient trends or weather patterns, you will work to solve real world problems for the industries transforming how we live.
Your Role and Responsibilities
As part of IBM GTS Infrastructure services (IS), Resiliency Orchestration (RO) team is responsible to build software product, applications, data and infrastructure resiliency automation software and services for IBM enterprise customers having their applications spread across traditional systems, private cloud and public clouds like IBM, AWS, Azure and GCP.
The GTS IS team is seeking a Data Scientist.
You will be working with an amazing team to execute and deliver analytic solutions.
The right candidate will be excited by the prospect of optimizing or even re-designing our anomaly detection and correlation models.
The solutions developed by you would be highly scalable and will be deployed on platforms like Kubernetes, VMware and public clouds.
You are a great fit if you can:
Dissect business problems and devise analytical solutions
Collaborate with experts in a business area, getting an understanding of the underlying business process, strategy and execution
Identify approaches to improve model accuracy and effectiveness of analytics
Define output of use cases for end user consumption to perform optimization analytics
Address business needs by prioritizing critical pain points that, once solved, will drive the most value
Extract, transform, and combine all incoming data with the goal of discovering a previously hidden insight, which in turn can provide a competitive advantage or address a pressing business problem
Not just simply collect and report on data, but also build statistical models, determine what they mean, then recommend ways to apply the data
Derive business insights through expert mathematical, analytical and computational techniques
Design, deploy, and tune
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