Job Title: Director Analytics
Experience: 14+ Years
Job Location: Remote, India
Company Overview
:
As Ensemble Health Partners Company, we're at the forefront of innovation, leveraging cutting-edge technology to drive meaningful impact in the Revenue Cycle Management landscape. Our future-forward technology combines tightly integrated data ingestion, workflow automation and business intelligence solutions on a modern cloud architecture. We have the second-largest share in the RCM space in the US Market with 10000+ professionals working in the organization. With 10 Technology Patents in our name, we believe the best results come from a combination of skilled and experienced team, proven and repeatable processes, and modern and flexible technologies. As a leading player in the industry, we offer an environment that fosters growth, creativity, and collaboration, where your expertise will be valued, and your contributions will make a differenc
e.
Position Overvi
ew:The AI solutions architect is responsible for building AI and Machine learning models and pipelines, with a focus on generative AI, LLMs and predictive modelling. The successful candidate will work closely with business owners to understand their data requirements and product specification in order to help them make data-related decisions and product design choices. The role will also require close work with data scientists, software engineers and developers to deliver solutions. Another crucial part will be defining the strategic priorities for AI and GenAI development across the company and educating both technical and business teams about the latest development in AI. The job role may also require you to learn new tools and technologies fast, which will be well supported by in-depth ML/AI knowledge as well as basic programming and scripting skil
ls.You should have expertise in the design, development, management, and maintenance of systems and handling of large datasets. You should have hands-on experience with common machine learning and AI frameworks, and a good knowledge of AI and machine learning fundamentals (deep learning, regression, classification and clustering algorithms), retrieval augmented generation pipelines, as well as a good grasp of the design and evaluation of LLM-supported use cas
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