Subha M.

Note: Pls scroll down to the end to see my employment history ⦿ Work: I assist small to mid-sized enterprises with data engineering, business intelligence, and visualization/Reporting. I don’t believe in a one-size-fits-all solution for Data Management. I help my clients make the right choice. After completion of a project, I provide detailed documentation to enable you to continue maintaining your data product(s). ⦿ My Skills: Data Visualization/Reporting Tools: Tableau, SSRS, Cognos 10.2, Cognos 11.1 Analytics,Google Data Studio, Grafana Databases: SQL Server, mySQL, postgreSQL, Azure, AWS Redshift Cloud Technologies: AWS AppFlow, AWS S3, AWS Lambda ETL Development Tools: SSIS, T-SQL, Cognos Framework Manager, Cognos Transformers Coding languages: Python, R Agile Project Management Platform: Atlassian (JIRA) Source Control: Git Survey Tools: Qualtrics No Code/Low Code Workflows: Zapier, Notion Data Sources: IBM MAPICS, Google Analytics, Epicor, Anaplan, Google Sheets, CSV/Excel files, Microsoft SQL Server, PostgreSQL, S3, Redshift, RDS API Integrations: Mixpanel, Twilio Segment, CustomerIO, Posthog, Salesforce, Qualtrics, Stripe, Saleor, MedusaJS ------------------------------------------------------ ⦿ Work Highlights: • Designed and set up the entire Redshift database architecture, and built cloud data pipelines to integrate tools like Mixpanel, Segment, Customer.io for seamless analytics ingestion. Also set up data pipelines from order management systems such as MedusaJS and Saleor. • Developed an image-processing algorithm using OpenCV and Python. • Developed a workflow using Notion and ChatGPT to generate detailed scripts for social media advertising. • Used Zapier to integrate multiple APIs to trigger jobs and to post data onto platforms. • Created dashboards with Grafana and Tableau, enabling stakeholders to monitor KPIs and take data-driven actions. • Automated reporting workflows using Microsoft GraphQL and custom Python scripts. • Architected an end-to-end Azure reporting solution, automating SFTP ingestion and email-based report distribution. • Custom built call center analytics performance tool to reduce call volume using Python & Tableau. o Built a tool in Tableau comprising multiple dashboard views where users could decide the type of comparisons they wanted to see. o Built Python scripts to pull raw data from multiple Google Analytics properties periodically, combine data and feed the data to Tableau on a schedule. o Used AWS AppFlow and AWS S3 to export data from Salesforce on a schedule. Built Python scripts to clean this data and run multiple machine learning algorithms (Ensembles) to perform Sentiment Analysis. The Python scripts were setup to allow for constant training based on verified data. This data was then fed to Tableau on a schedule. • Developed Dashboards in Tableau to gauge Chatbot effectiveness • Used AWS AppFlow to gather chatbot data and store it in S3 for historical tracking. This data was then visualized for various metrics like Retention Rate, Chatbot Conversation Length, etc. • Performed Hypothesis testing to determine the chatbot's launch effectiveness (i.e., to determine if the introduction of the chatbot had a significant effect on call volume reduction) • Developed a Chatbot in Python for ticketing (NLP, chatterbot libraries) • Used Python NLP algorithms and libraries to build a chatbot that could answer queries related to ticket booking and could retrieve booking details. • Developed Dashboards in Tableau for Non-profit research based storytelling • Mined survey data from Google Sheets and developed dashboards in Tableau to relay the stats related to a certain social cause. • Developed stored procedures and SQL views using SQL Server, SSIS and T-SQL for a large beauty company. The 'Revenue Recognition' logic was incorporated in the report development so that revenues could be realized only after being invoiced. Developed the necessary processes to deploy the reports to top executives to their emails. Developed reports using Cognos Analytics and SSRS. • Developed Predictive Analytics algorithms in R and Python across domains. • I have also worked on Predictive Analytics use cases (supervised & unsupervised) in R and Python. ----------------------------------------------------------------------------------- ⦿ Availability: I am in Stamford, CT and work in any US timezone. If you have a requirement for a different timezone, we can always discuss it.