As a Business Intelligence Engineer at RingCentral, I utilized structured data to build dashboards that enabled data-driven decisions. Leveraging my analytical thinking and predictive analytics skills, I collaborated with cross-functional teams to merge business education with hands-on technical expertise. • Developed data-driven dashboards for strategic decision-making• Utilized analytical thinking and predictive analytics for business insights• Collaborated with cross-functional teams to merge business education with technical skills

• Built category specific reports to be run on a scheduled or as-needed basis to inform and drive category savings levers (e.g., historical spend trends, cost increases, volume spikes, etc.).• Align with the Category Manager to create and automate Procurement standard reporting for category related KPI to measure, control and benchmark procurement processes including creation of recurring metrics reports• Used forecasting techniques (predictive analytics) for spend forecasting to integrate the proof-points by comparing past experiences to predict the future plan of spend management.• Provided regular reporting on OLA and SLA metrics, identifies outliers and investigating the reasons for such occurrences.• Collected / Organized / Prepared / Managed data for analysis, and conducting quality checks to identify and highlight inconsistencies in datasets and suggested resolve on a timely manner• Identified savings opportunity based on spend data and worked with team to achieve those targets using tools such as R/Python for data analysis• Built dashboards using Tableau and in GEP which enables manager to efficiently track, evaluate, and optimize all acquisition processes within a company with the help of KPIs such as the compliance rate, purchase order cycle time, spend across categories and subcategories, new supplier acquisitions and supplier defect rate, and many more

• Conducted data mining, data modelling, statistical analysis, business intelligence gathering, trending and bench-marking. Utilized R and Python statistical software to track and analyse data• Optimized data collection procedures and generated reports on a weekly, monthly, and quarterly basis and reports for implementation of marketing strategies. Experience in Retail and E-commerce domain, having worked on Sell Thru Analysis, Inventory Optimization and Product Rationalization• Translating numbers into meaningful facts for businesses to help them make better business decisions using various visualization tools such as Tableau and Excel• Dealing with sales figures, market research, logistics, and/or transportation costs, among other things.• Created reports and visualization on Sell Thru Analysis, SKU Rationalization and Inventory Optimization. Times Series Modelling for Inventory Data to predict future stock of articles required to be present in Inventory to meet the demand of the customers

• Gathered, defined business requirements to improve business processes.• Translated the requirements into systems solution by preparing functional specifications and technical requirement document.• Followed the Product Life Cycle Management including Business process mapping where by Identify business core/critical system/processes.• Interacted with higher management team and associates to facilitate smooth communication to understand and analyse the requirement and also identified appropriate solutions for problems, if any• Reviewed literature for designing frameworks, collecting and analysing data• Created the survey questionnaire for 3PL companies as part of projects on their target market for launch of new products.• Conducted extensive primary and secondary research for projects• Suggesting and executing improvements in Business processes of the organization

• Study and analysis of Contract Labor Agreements • Identifying and documenting points of improvements• Suggesting improvements to increase productivity based on “Time and Motion Study” analysis