Founder
2018 – PresentUpper Delta
Founded a specialized consultancy focused on data science and machine learning, leading projects in telecom, finance, analytics, and research-driven delivery while mentoring teams and shaping strategy for clients.
Key projects
- Product recommendation system for a large telecom. Built a content-based recommendation engine from scratch to support upsell strategy, combining product usage, billing, customer interaction, demographics, and pricing signals. The system was validated through A/B tests, producing a statistically significant uplift in average revenue per user.
- Quality of service degradation prediction for a telecom operator. Built a large-scale monitoring and anomaly detection solution that processed technical network metrics and semi-structured logs across millions of devices. The system identified customers likely to experience service issues and helped the engineering team act on root causes.
- Rooftop obstacle detection for a solar energy company. Created a computer vision workflow using satellite imagery and building-footprint records to identify suitable rooftop sites for solar panel installation, outperforming individual human labels on the initial milestone.
- Sales forecasting for a beverage company. Implemented a forecasting system that projected SKU-level sales for the next three months at each point of sale, enriching data with external variables such as weather, demographics, and events. The output was delivered via a geographic dashboard for business users.
- Data lake implementation in AWS. Designed and maintained a data lake supporting bulk and streaming ingestion from brokers, product usage logs, SaaS systems, and APIs. The platform supported analytics, operations, product, and AI workloads at scale.
- Automated valuation model for real estate. Developed, deployed, and monitored an internal valuation system for over 140 million US properties, integrating tax, census, permit, and satellite data with scenario simulation for renovation advisory.
- Quantitative stock movement prediction and automated trading infrastructure. Built a predictive modeling platform combining technical indicators, proprietary datasets, financial statements, earnings reports, and third-party market feeds, with automated ingestion and data-lake support for structured and unstructured financial data.
Methodology
- Embedded technical leadership. Integration within client teams with ownership of key technical decisions, translating business goals, requirements, and preferences into clear, actionable plans.
- End-to-end delivery. Coordination and hands-on execution throughout implementation, maintaining a high bar for engineering quality.
- Team development. Close collaboration as a member of the team, sharing experience, mentoring colleagues, and building lasting internal capabilities in machine learning and AI.
- Long-term partnership. Deeper business context enables higher-impact recommendations, while sustained collaboration ensures those recommendations are translated into reliable production systems.