Working with the Market Intelligence team to provide analytical aid to look into the feasibility of new site launches in terms of workforce availability using machine learning algorithms like clustering.Analyze the socio economic factors to gain insights on the labor market KPI's.Determine the capturable workforce using the occupational history and competitor intelligence.Perform Natural Language Processing on the relevant information to gain intelligence on the competitive edge in the given market.Job responsibilities include helping create data pipelines, research into demographic data which could help enhance machine learning models.

• Strengthened analytics team to aid Brand Management and R&D teams to understand the market potential for new products and market competitor trends using 3rd party data from IRI and NPD.• Introduced and formulated new dashboards to analyze marketing/promotional efforts in Power BI by defining metrics like sales lifts, market penetration, and post-promotion customer retention using DAX.• Design and generate robust reports using Power BI, SQL, and Excel to provide actionable insights and visibility into the vendor performance and correlation of the same with the item dumps at warehouses.• Train and guide the managers and employees on creating and optimizing Power BI reports and help migrate the legacy reports to Power BI.

-Worked to maintain Data Integrity and helped data cleaning for better and accurate business operations.Performed survey analysis and created KPIs to extract meaningful information from the surveys.-Analyzed marketing efforts to find the most effective marketing channels

• Work closely with Utility Smart executives and the software development team to bring data analysis support to the company’s services. • Contributing to Utility Smart’s ‘Smart Assistant’ to create business performance and resident billing dashboards for the management, customers, and the residents using smart devices by processing intents and metrics using Amazon Lex, and Google Dialogflow.• Designed and created Utility Smart's Invoice Validation Tool using analysis of utility provider rate structures to recalculate invoices in real-time to maintain data integrity by catching provider and Utility Smart errors. The tool is a custom web app interface made for team members to use the solution created using Excel, SQL Server, and Python.• Created a prediction tool for budgeting Utility expenses on new upcoming properties for multifamily management companies using different predictive modeling techniques in python. • Created a Utility Budgeting and Accrual Tool for Utility Smart's multifamily property management clients by implementing forecasting techniques using both historical and benchmark data sets.

• Optimized Arizona Lottery’s Paid Media Mix by identifying campaigns with the highest revenue impact.• Developed a feasibility proposition for the launch of a high-value ticket of $50.• Designed an optimal product mix for the 'Fast Play' line of products.• Analyzed the demographic composition of the Players Club base for more targeted offers.

• Working on Attribution modeling framework for FetchRev (marketing startup) to find optimal promotional strategies. Applying NLP to perform customer segmentation to make the promotions more targeted according to user preferences hence reducing waste.• Analyzed the coupon text used for the promotions in python, to create clusters (using K-means and silhouette Analysis) of similar businesses by finding the cosine similarities between the promotions.• Used the business clusters to categorize the subscribers according to their interests by using the coupon redemption data.• Analyzed the coupons using LDA to find the most effective words that drive the interest of customers in each business cluster.• Analyzed the coupon effectiveness by analyzing the conversion funnel and working on creating a multivariate test for successful promotions.

• Optimized Inventory and existing transport pipelines in Honor health facilities to reduce the on-demand delivery costs and logistics costs by 20% (of $1.6 million), also created new transport pipelines by analyzing previous years data to find trends in demands across different departments and routes using Tableau and python.• Used python to do data cleaning for addresses and other string discrepancies for better analysis.• Created visualizations using tableau to identify consistent trends in demands and focus areas for cost reduction.• Applied Pareto’s 80/20 rule to identify the most costly routes and primary cost reduction areas.• Used Google Cloud Platform’s geolocation API to find the coordinates of the locations to build a path optimizing model which could potentially reduce costs by an additional 15%.

• Assisted clients in addressing complex business problems in the agricultural industry through the application of relevant technology and helped increase the revenue by $500,000.• Reduced transaction time per customer from 70 seconds (manual transaction) to 12 seconds (digital transaction) increasing the operation speeds by 83% helping in the increase of business capabilities. • Reduced the warehouse operations cost by 10% through analyzing the inventory data for warehouse space optimization using SQL for generating reports based on seasonal produce.• Developed Android (Java) and web platform (TypeScript) for monitoring and analyzing crop health, which helped in crop protection and reduced the crop mortality rate by 15%.