CELESTIN JACOB

Hotspot Analytics

• Identified health of Customer Experience & Support business based on indexing its KPI and Dimensions across Preparedness, Responsiveness,Resolution and Customer Experience Segments.
• Developed Digitized platform which enables detection of hotspots and their drivers which lead to reduce of 90%(~1250 man hours/ week) of manual efforts in identifications of Hotspots, also provide actionable insights for leaders to create remediation plans.

Health Care Industry Index

• Identified the potential health care providers for the product recommendations with their revenue and other 576 KPI's.
• Fuzzy Selector was used to map the health care providers associated with the customer base. PCA ( Principal Component Analysis) and Correlation as a 2 step process to variable selection.
• Clustering ML Algorithm (K means Clustering) was used to categorize the health care providers based on several aspects (Revenue, EBITDA etc.). Developed a dashboard which enables the recommendations for the health care providers which lead to the increase of revenue around 8% ($ 1.37 million).

Customer Satisfaction Score Driver

• Built ML base MW simulation tool that predicts Customer Satisfaction when Staffs are laid off, performing user acceptance testing (UAT) to validate user requirement and expectation. This led to the saving of 9 efficient staff and got rid of staffs with poor performance.
• Build Customer satisfaction Driver Model to predict the future cast by manipulation drivers which led to CS Score from 4.3 to 4.5.

Adhocs/Dashboards

• Collaboration Dashboard - Power Bi,SQL,ADLS,Azure Data Factory. Developed actionable report for tracking changes in collaboration events of tickets handled by engineers and its time taken which helped the leadership team to start different initiates across different business unit and service offerings. This report also helped in tracking the efficiency of the employees thus validating their skillsets.
• Customer Churn Analysis - Power Bi, Excel, Powerpoint. Performed statistical analysis to understand the possible reasons for Customer Churn based on consumption & Support KPIs to provide actionable insights for the leadership team to create remediation plan.
• Monthly analysis of important KPI's for the business at monthly basis and adhoc analysis on the requirements of the clients to answer business questions.

Feature Detection For Cement Strength
• Identification of key parameters leading to strength of cement
• Builded and Tested - XGBoost, Random Forest, Linear Regression, Lasso, Ridge
• Checked multicoltinearity performed PCA and took the model accuracy
• Performed K means clustering and Checked the accuracy using various models
• Evaluated model and Hyperparamater tuning for best accuracy

Medibuddy prediction of amount spent on Insurance Claim
• Business Analysis and identification of key parameters leading to insurance purchase
• Builded and tested - Linear Regression, XGBoost,Random Forest, KNN
• Evaluated model, Performed PCA and Hyperparameter tuning for best accuracy