marketing, legal, claim investigation, tele sales, etc. Managed minimum 2 resources directly while delivering projects. Regularly updating to stakeholders and delivery in CXO meetings
●
Marketing
oAnalyzed customer engagement campaigns and generated insights, presented in quarterly
CXO
meetings[Technologies used-
AWSAthena (SQL), Tableau]
oCreated an analytical model that reviews past performance to determine how each marketing mix element contributes to sales and identify the channel driving
maximumROI
[Technologies/techniquesused-
Mediamix modeling, Python, R, Excel]
oDevised a framework to derive customer affluence to
cross-sell
rightproduct to the given customer group [Technologies/techniques used
Speechto text, Text analytics, AWS Athena (SQL), Tableau, Excel]
oDesigned data lake structure to track cross-sell conversions, engagements and customer feedback o Identified best product combinations for cross-selling by comparing health insurance products, built correlation matrix based on feature overlaps o Analyzed agent calls using speech to text and text analytics to assess effectiveness of cross-selling
●
Legal/ Motor claims
oCreated predictive model to determine right course of action for third party motor claims (whether to settle or contest) [Technologies used
Tableau,R, Python, Azure ML designer studio]
oDevised a logic to explain the prediction (output) by providing probable indication parameters o Analyzed more than 350 variables of investigation report in order to deliver this model o Created pipeline and deployed a real time model on azure platform o Created clustering model to classify a customer driving behavior which helped as an additional underwriting variable [Technologies/techniques used-
PAMclustering, R, Python, Excel]
●
Healthclaims
oCreated analytical model to predict disallowances (which company is not liable to pay customer on claimed amount) at the moment of claim intimation to reduce the discharge process TAT for an end user [Technology/technique used-
Tableau,Python, R, Excel]
●
Customersupport & tele sales
oReducing inbound calls at customer care services [Technologies/techniques used-
Speechto text, Text analytics, Tableau, Excel]
oInbound calls were analyzed to understand frequently asked queries by customers o Customer demographics were analyzed in order to find out key pain areas to reduce frequency of calls by spreading awareness of claim processes with customized communication
●Apart from above mentioned projects, found opportunities of automating the repetitive processes and created automation pipelines on azure, Mentored new joiners with their projects.