System and method for data science model scoring

A computer-implemented method to facilitate data science model score management for an enterprise, comprising:

• receiving, at a computer processor of a data science model score server from a user via a remote user device, an indication of a selected data science model;
• retrieving, from a data science score database, information about the selected data science model, wherein the data science model score database contains encrypted electronic records, each encrypted record including a data science model identifier and a set of data science model scores generated for the enterprise;
• based on the retrieved information, automatically calculating a maturity score for the selected data science model in accordance with a scalable score, a service-oriented score, a validated score, and a productized score;
• receiving from the remote user device an adjustment to at least one of the scalable score, the service-oriented score, the validated score, and the productized score;
• responsive to the adjustment, automatically re-calculating the maturity score for the selected data science model;
• providing evaluation feedback to a machine learning process so that the scoring weights can be automatically improved;
• transmitting data to the remote user device in support of a graphical user interface including a reporting dashboard with a radar chart plotting current data science model values including:
• an automation rubric value, an execution rubric value, and a performance rubric value, wherein the plotted current data science model values plot a shape having an area and the area represents an overall maturity score for the current data science model;
• and
• automatically establishing communication links via an email server and a calendar application to provide data science model reports and alerts to the user.

A non-transitory computer-readable medium storing instructions adapted to be executed by a computer processor to perform a method to facilitate data science model score management for an enterprise, the method comprising:

• receiving, at a computer processor of a data science model score server from a user via a remote user device, an indication of a selected data science model;
• retrieving, from a data science score database, information about the selected data science model, wherein the data science model score database contains encrypted electronic records, each encrypted record including a data science model identifier and a set of data science model scores generated for the enterprise;
• based on the retrieved information, automatically calculating a maturity score for the selected data science model in accordance with a scalable score, a service-oriented score, a validated score, and a productized score;
• receiving from the remote user device an adjustment to at least one of the scalable score, the service-oriented score, the validated score, and the productized score;
• responsive to the adjustment, automatically re-calculating the maturity score for the selected data science model providing evaluation feedback to a machine learning process so that scoring weights can be automatically improved;
• transmitting data to the remote user device in support of a graphical interactive user interface including a reporting dashboard with a radar chart plotting current data science model values including:
• an automation rubric value, an execution rubric value, and a performance rubric value, wherein the plotted current data science model values plot a shape having an area and the area represents an overall maturity score for the current data science model;
• and
• automatically establishing communication links via an email server and a calendar application to provide data science model reports and alerts to the user.