Experience | Bikash Sapkota

Jan 2025 - Present: Big Data Engineer (GeoSpatial) at LocationMind, Tokyo, Japan

Building mobility and geospatial data pipelines that transform raw GPS-scale inputs into people-flow analytics, map-ready outputs, and decision products.

Highlights: Design ingestion, validation, normalization, aggregation, and geospatial enrichment workflows for mobility datasets. Build time-series and spatial features for people-flow analysis, dashboards, maps, and CSV data products. Improve reproducibility, monitoring, performance, documentation, and governance across the data lifecycle.

Skills: Python, Spark, AWS, Geospatial joins, Time-series features, Data quality

Nov 2021 - Jan 2025: AI Engineer at GridSolutions Inc, Tokyo, Japan

Delivered optimization and integration systems for energy pricing workflows, including business logic, APIs, and OpenADR VEN projects.

Highlights: Implemented optimization modules using Mixed-Integer Nonlinear Programming for pricing strategy workflows. Built API interfaces for client-platform integration and maintained OpenADR VEN projects. Refactored architecture to reduce single points of failure and improve operational reliability.

Skills: Python, Optimization, MINLP, OpenADR, API design, Reliability

Nov 2019 - Nov 2021: Machine Learning Engineer at Bottle, Kathmandu, Nepal

Led delivery of machine-learning-backed APIs and cloud services, bridging implementation architecture with client-facing product needs.

Highlights: Led end-to-end project lifecycles from planning through production delivery. Collaborated with architects to define implementation plans aligned with client constraints. Developed REST APIs and cloud integrations that exposed ML functionality to applications.

Skills: Machine learning, REST APIs, AWS Lambda, Amazon EC2, Team leadership

Jul 2018 - Nov 2019: Machine Learning and OCR Engineer at Smart Data Solutions, Kathmandu, Nepal

Built OCR and document-intelligence workflows for scanned claims, combining extraction, classification, and operational interface improvements.

Highlights: Extracted characters from scanned claims using Tesseract, FineReader, and Cartouche. Classified extracted text with Random Forest models and extracted entities using rules and NER. Improved manual keying interfaces to reduce operational friction.

Skills: OCR, Tesseract, FineReader, WEKA, Random Forest, NER