Rohan Jha Email & Phone Number

San Jose, CA, US

Equip BILL's platform with the best-in-class document understanding capabilities leveraging state-of-the-art AI technologies to maximize value to SMBs.

Helped prototype and develop an MVP for an early-stage startup in the Supply Chain sector. Main contributions were in developing an enterprise-grade demand forecasting solution coupled with a RAG application to provide business value to supply chain planning teams.

San Francisco, California, US

• Managed data science & engineering teams for the Supply Chain AI SaaS product for 5 CPG customers. Forecasted unconstrained demand employing multiple forecasters (statistical methods and gradient boosted machines) and.
• Partnered with product and customer success leadership to establish key performance indicators, resulting in a 15% improvement of trial subscription conversions.
• Designed and implemented the end-to-end deployment playbook for the demand forecasting module, streamlining processes, and reducing deployment time by 30%.
• Collaborated with cross-functional teams to identify and address critical business challenges, leading to a reduction in forecasting errors by 10-15% through implementation of automated model refreshes and performance.
• Provided mentorship to data scientists on my team, fostering their professional development and facilitating their advancement within the company.

San Francisco, California, US

• Led a team of data scientists and engineers to develop the Asset Health AI product which drove substantial asset maintenance cost reductions of ~20% at two steel plants. Implemented an advanced anomaly detection.
• Spearheaded initiatives to standardise model training workflow (including onboarding the ML pipeline onto Kubeflow) improving developer efficiency by 4x.
• Interfaced directly with customers, including executive sponsors and plant managers, to deliver compelling results and articulate technical details with clarity at all levels.

San Francisco, California, US

• Lead data scientist and product owner of an energy prediction application designed for electric arc furnaces (EAF) at steel plants.
• Developed random forest models to accurately forecast energy consumption across multiple sections of steel plants and innovated an optimal trading strategy that achieved up to 10% reduction in energy costs and.

New York, New York, US

• Developed a data orchestration pipeline for running end-to-end automated regression tests enabling seamless reconciliation of all client reports and reducing manual testing effort by 3x.
• Led a strategic internal initiative to revamp the data archival strategy, overseeing the migration of all transactions and account data to ATMOS cloud storage for enhanced historical reporting capabilities. Achieved a.

New York, New York, US

• Designed and implemented a graph-based comparison and impact calculator for the Prime Brokerage reporting framework, successfully preventing user errors in report modifications and significantly reducing support costs.
• Upgraded the reporting platform used by the Prime Brokerage business to use REST architecture and improved the daily SLA of client reports by 1 hour.
• Devised a new format of reports using SQLite (file-based database) as a requirement to support the prime brokerage reporting dashboard.

• Co-founded a start-up to create original educational content for robotics workshops for university students.
• Successfully held workshops at 2 universities for 200+ students to build autonomous maze-solving robots.

Master’S Degree, Machine Learning And Data Science

Bachelor'S Degree, Electrical And Electronics Engineering

High School