Job Description :
Must have

Services- Analyze data (Large Data sets ), preprocess data , data visualization, reporting

Languages/Level- SQL, Advanced Python Intermediate

Libraries/Levels- Python : Json basic ; Numpy , Pandas ,scikit Learn , Matplotlib-Intermedidate.

GCP Products / level- Big query – Advanced ,CAIP- intermediate , dataflow- intermediate

Non GCP Products / level- ML:NLP , supervised , unsupervised learning (Clustering)

Scope of feasibility Study

- Understand the data and associate data models that the customer uses to store billing history .

- Determine the best approach to represent discrete billing “states” in other words , a given customer’s billing history should be represented by some state space e.g., every month there are set of variables – data uses minute used, text sent roaming charges etc.

- Assess if there is the possibility to find correlations between 1) moving from one billing state to another and 2) a billing related inquiry being made in contact center . also understand if the data is available ,joinable etc.

- Assessing how could we determine the highest frequency of billing state or group of similar billing state , this may involve the use of clustering . the objective is to understand which billing state /events to prioritize for CCAI support via virtual agents.