CKM Analytix

T-K from CKM Analytix makes sense of your operational data, increasing efficiency by 40-50% while simultaneously improving service quality and mitigating risk.

Headquarters

New York, NY

Size

51-200 Employees

Industry

Information Tech

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Description

We believe our number one asset is our people, who shape the uniquely creative and energetic culture at CKM. We are passionate about knowledge sharing and professional development, and we give ample opportunities to satisfy natural curiosity and the autonomy to make your own choices about the trajectory of your career.

CKM Analytix is a recognized leader in leveraging advanced data analytics for performance improvement. Our approach utilizes direct digital empirical measurements to assess employee productivity, resource utilization, process efficiency and to leverage impactful and ROI driven AI and ML in the management of service operations. Our assessments are quickly morphed into data science driven applications yielding measurable improvements.

Our teams are mostly composed of cutting edge data scientists and DevOps engineers - holding PhD, MSc and BSc. Our teams are organized to maximize the development of data science experts operating across multiple competencies to meet our clients' needs.

CKM sets itself apart from other major players in the data analytics space by being technology agnostic. Our primary objective is solving business problems through data science. Achieving meaningful performance improvement with data science requires extensive experience dealing with all the nitty-gritty details in identifying, gathering, wrangling, normalizing and managing unwieldy structured and unstructured datasets. We master all aspects of data ingestion, advanced analytics, and development of impactful data science applications - this is where CKM thrives.

We share our advanced knowledge in data science by performing pro-bono projects for different not-for-profit organizations.

From our bases in New York and in London, we serve clients around the world.