AI and Legal tech

AI and business intelligence

• Developed algorithm in Python to scrape different sources for KPIs under IBM Hybrid Cloud and pushed metrics to a remote server to reduce the bottleneck in the product pipeline

• Used Jenkins and Github API to poll for data used in algorithm's for KPIs required by different teams in the development phase of product

• Set up Prometheus database to push data calculations and placed the tool on a Firebase server

• Visualized KPIs on Grafana dashboard and improved the CI/CD by helping product managers better interact with customer issues, and helping software architects focus on better code delivery and production

• Developed machine learning algorithm in Python for root causes detection to assist Hybrid Cloud SAE (service availability engineers) team offerings

• Polled monitors for metrics data and Grafana dashboards for root cause analysis

• Implemented time-series database with InfluxDB in architecture of CEM offering and used domain knowledge for feature engineering before using neural networks for machine learning decisions

• Created dependency map for service availability engineers to use during on call outages

• Used Python for data analysis on service parts for the supply engineering team, including forecasting and part dependencies for worldwide service centers to order and phase out parts

• Assisted in cleaning data and created a dashboard for Project Managers to add new parts to the internal database and error checking algorithm tio make sure only desired parts are appearing on internal ordering page

• Created virtual reality tour and experience of new Tesla models and Fremont factory for potential Tesla customers