Utilize advanced data science techniques to classify and categorize professional liability claims into buckets of clinical and non-clinical, as defined by the Chief Medical Officer (CMO) and Chief Data Officer (CDO) 2. Work with the CMO and CDO to refine the categorizations to an acceptable error rate, specifying when more training data may be necessary 3. Work with the VP of Technology to productionalize classification model 4. During the course of this consulting arrangement, all code will be uploaded to Github on a weekly basis with appropriate notations 5. Upon expiration of this agreement, or termination by either party, consultant will provide a walk through hand off as well as documentation of all models utilized to classify and categorize claims Utilize advanced data science techniques to classify and categorize professional liability claims into buckets of clinical and non-clinical, as defined by the Chief Medical Officer (CMO) and Chief Data Officer (CDO) 2. Work with the CMO and CDO to refine the categorizations to an acceptable error rate, specifying when more training data may be necessary 3. Work with the VP of Technology to productionalize classification model 4. During the course of this consulting arrangement, all code will be uploaded to Github on a weekly basis with appropriate notations 5. Upon expiration of this agreement, or termination by either party, consultant will provide a walk through hand off as well as documentation of all models utilized to classify and categorize claims
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Education Level
No Education Listed
Number of Employees
251-500 employees