Alina Chapaeva

Achievements: -Delivered 3 phases of a lab-software consolidation roadmap, reaching $15K run rate and 25% ROI in 10 months; projected $630K benefit on $320K (97% ROI) by 2028. -Integrated two R&D systems, improving data flow for 20 users and cutting manual work. -Automated KPI reporting with Python and BI, delivering dashboards that cut reporting time by 60%. -Reorganized dev & analytics teams during a transition, aligning processes with new priorities and mentoring engineering & analytics teams in Armenia.

-Built and optimized pipelines (Python, Kubernetes, REST API, PostgreSQL), improving traceability and data reliability in workflows. -Streamlined data flows between apps by integrating equipment (Dako stainer, Illumina NovaSeq X), Python microservices, Google APIs, Jira REST API and event-driven services. -Deployed, monitored, maintained app/pipeline infrastructure for LIMS upgrades and rollout of a cloud biotech R&D platform, producing regulatory-ready technical documentation.

-Developed a $150K e-commerce analytics solution. -Built and maintained a standardized database of 10,000+ retail outlets, improving data consistency and audit transparency across analytical workflows. -Delivered PepsiCo’s first custom analytics report. -Automated data processing and forecasting for P&G’s “100 Golden Stores.” -Created a COVID-19 sales heatmap shown at a national conference. -Developed secure cross-market reporting and reduced manual classification by 75% with an internal classifier.

- Developed and launched a country-focused geo-analytics product that transformed location data and Python-based geospatial and clustering models into clear, revenue-driving insights. - Designed the product architecture, built a scalable data pipeline, and created heat maps highlighting high-potential locations and white-space market opportunities.

Processed transactional datasets and supported the development of an NLP classifier for receipt item categorization, leveraging TensorFlow and PyTorch models.