Ravish Sharma

Working with different functional teams globally to deliver advanced analytics projects. Led cross-functional teams to deliver advanced analytics projects, enhancing business decision-making.

IVR Self-Serve Success/Failure Model for Customer Care: (Xgboost)

• Developed a classification model to predict whether the customer will be able to self-serve or not (~80% PR-AUC score).
• Important features identified from the model were used to improve the various data quality items so that the self-serve rate can be improved.

Email Engagement Driver Analysis and Email Feature Optimization - (LightGBM and SHAP):

• Created ML models to predict opens and clicks for email deliveries with approximately 85% and 75% PR-AUC scores. Extensive use of feature engineering and the LightGBM model for predictions.
• Identified email features using SHAP to increase engagement, collaborating closely with marketing teams..
• Implemented a method to optimize the email features according to customer preferences, and assembled emails that lead to a higher engagement rate.

Identify fraudulent glucose meter placement using a classification model: (XGBoost)

• Developed a model to identify in which territories fraudulent glucose meters were being placed, with a PRAUC score of approximately 75%.
• The predictions from the model were used to flag the territories that had fraudulent meter placements for further investigation.

Head of Business Insights and Data Requests: (Tableau)

• Managed system architecture design, driving improvements across multiple applications.
• Managed cross-functional teams to ensure timely project delivery and collaboration.

Worked with a MedTech client in diabetes care market for EMEA and APAC geographies (~15 markets across the globe). Directed a team of 10 members in strategic analytics initiatives, impacting sales and marketing strategies.

Promotional Response and Marketing Mix (Generalized Linear Models):

• Calculated the impact of promotional channels on sales for multiple clients using Linear Regression models.
• Used various techniques, like ad stocking, variable transformation, and carry-over, to mimic the actual behavior of various promotional channels in the regression models.
• Derived the optimal marketing mix for clients using the promotional channel impact obtained from the PR exercise.

Sales Force Effectiveness:

• Developed automated excel dashboards for EMEA and APAC markets to track salesforce and sales performance. Identified key metrics to drive sales force effectiveness across 15 countries and summarized it for the global leadership.
• During Covid’19, developed an automated excel dashboards for all markets to keep a weekly track of remote calls, field calls and unutilized capacity. This helped the client in real time tracking and decision making.
• Designed SFDC adoption report for the markets to track the SFDC compliance of the team. Worked on territory design exercise to restructure the territories based on workload, potential, geographical size, and rep locations.

Sales Analytics and Sales Incentive Compensation (IC Plan):

• Calculated sales target at rep level using national level business plans. The sales targets helped the client in finalizing the sales incentive compensation (SIP) plans for the account managers.
• Performed IC goal fairness testing in Germany and France to support worker’s council discussions related to hypothesis on unfair/bias approach. Developed an excel tool for calculating quarterly and annual bonus payouts across the globe based on sales incentive plans.
• Created automated sales reports for various geographies to capture client’s sales and performed competitor analysis at global, national, territory and brick level.