Jan 2015 – Aug 2016 · 1 yr 7 mos

• Apprentice leader role is about leading the teams in terms of solving the right problems for the clients, capability uplift, developing the individuals that make the team and contributing to the growth of the organization.
• Lead a team of ~30 people working for a leading Australian Banking and Insurance Corporation. The analytical work spreads across various areas of Claims, Distribution, Products etc. Also responsible for driving the growth for the team in this analytical space
• Predicting claims risk, Estimate deviation, Claims transformation, Claims loss analysis, Distribution performance etc. are some of the major areas where data is leveraged to enable the client teams to make better informed decisions.

Sep 2013 – Mar 2014 · 6 mos

• Performed the associate role for a period close to six months and coordinated with the Client and India teams to ensure high value for business was driven through the project
• Leading Australian Banking and Insurance Corporation
• Profitability framework
• Developing a profitability framework to understand the quality of the business other than just the quantity across channels, brokers, corporates etc.
• Built a visualization platform to ensure the information was easily consumed with the option to deep dive as per need to understand the underlying problems
• Enabled the clients to understand the true performance of the business and design required steps to maximize the value obtained

Jan 2013 – Dec 2014 · 1 yr 11 mos

• Lead multiple teams across domains to solve a wide range of analytical problems for the client teams. Responsible for various proposals and sales pitches for various clients in the organization
• Leading US Appliance Manufacturer
• Led a team of 10 members working across the areas of forecasting, data strategy development and sales driver analysis
• Time series and regression techniques were used to build robust models and deploy them into production
• Enabled the clients to make decisions on various fields by interconnecting results across the various client teams
• Global Payment Gateway
• Lead the analytical team for one of the world's leading payment gateway
• We worked with the client team to monetize the information that they had by jointly working on ideas that could help the end customers
• The first phase was developing a tool that helped the global sales team get the requirements from the clients and ensure the right set of products are made available to the team to service the clients effectively in a timely manner
• US Financial Corporation: Fraud Analysis
• The client was part of the US food stamp program and wanted to identify patterns that provide insights around fraudulent transactions
• Various characteristics of fraud were identified through research, first principles etc. to determine tests for them using the data
• A predictive system was then developed that captures a wide range of characteristics to identify potential fraudulent transactions
• Leading Australian Banking and Insurance Corporation
• Insurance: Customer Understanding and Attrition Analysis
• Developed a multinomial segmentation model using unsupervised machine learning algorithms to capture various behavior traits of customers
• Analyzed the patterns exhibited by the customers who cancel their policies and derived insights
• Leveraged the insights to build a predictive system to identify at risk customers, thus enabling the client to be more proactive in dealing with attrition

Jul 2011 – Dec 2012 · 1 yr 5 mos

• Leading UK online Fashion Retailer
• Developed marketing and trading dashboards enabling the team to make timely decisions on a close to real time basis
• Developed a forecast system to plan, forecast and maintain the optimum inventory for various SKUs across departments to reduce lost sales and inventory cost
• Analysis on various promotions during the holidays, product launches etc. to provide insights and make appropriate changes for maximizing business value
• Leading US Appliance Manufacturer
• Worked with the Spare parts division to understand the drivers for the sales performance and designing recommendations for the same
• Reviewed the entire data capturing mechanism to track the data elements that were not getting captured and the level of accuracy across various feeds. This led to a data strategy process to ensure the gaps were plugged in and use the right data effectively