Manish B

Conducted RFM (Recency, Frequency, Monetary) analysis at the product level to identify customer segmentation and product performance trends using python and K-means algorithm. Created marketing strategies tailored to distinct customer segments based on RFM scores, leading to a notable increase in company revenue. Facilitated seamless data access by promptly delivering requested data to stakeholders through Sql queries to cross-functional teams, including sales, customer support, logistics, and warehouses, ensuring they had the data they needed for their specific requirements. Conducted in-depth customer analysis, including retention analysis, tracking new vs returning customer trends, year-wise lifetime revenue analysis, and customer frequency analysis. Calculated growth percentages for key performance metrics such as orders, revenue, and customer counts and projected all the analysis in Power BI. Spearheaded initiatives to digitize operations, streamlining processes through the Hooper (Low Code) platform. Designed and developed multiple applications to replace manual data entry with automated data capture, significantly improving efficiency and accuracy in procurement and production operations. Managed Mojro, a major route optimization tool, to streamline route operations and ensure efficient data flow. Recognized the need for accurate geo-codes to enable geo-fencing within Mojro, prompting the implementation of database clustering techniques, such as K-means clustering, to enhance geo-coordinates for precise location-based services. Utilized Redash and Power BI to create a series of informative and visually appealing dashboards that provide valuable insights into various aspects of the business. Engineered and deployed Python scripts to execute queries automatically and populate spreadsheets, streamlining data extraction processes. Employed UiPath for additional automation initiatives, resulting in significant time and effort savings, enhancing operational efficie

Developed a robust forecasting model using a Random Forest Regressor. Achieved an exceptional 97% accuracy rate, showcasing my proficiency in predictive modeling. Developed and implemented Python scripts to automate data extraction processes, particularly when responding to cancellation requests from Redash.

Developed an automated application to see the number of Covid vaccinations done in GHMC-administered hospitals. Reduced the time required for the task from a few days to minutes, saving man hours for the organisation. Utilised UIpath for automation, AWS services(EC2,S3) as host and database and sent data via APIs to Bubble platform. Developed an automated application using UIpath to extract data from scanned pdf’s and generate spreadsheets. Performed Image Processing on the scanned documents and used OCR to extract information from them. The tool helped in reducing the time required for the task from 10 days to 2 hours per document. Created an automated system that gathers tweets and puts them in a spreadsheet. Applied Sentiment Analysis to the data in order to forecast its sentiment. It was communicated to the concerned officials based on the sentiment score.