Maksad Donayorov
Lead Data Scientist & ML Engineer
I build production ML and AI systems that drive measurable business impact.
Available for independent consultant work Lead Data Scientist & ML Engineer
I build production ML and AI systems that drive measurable business impact.
Available for independent consultant workAbout
With over years of experience spanning data science, machine learning engineering, and full-stack development, I partner with organizations to research, design, and ship production AI systems. I've led cross-functional teams of data scientists, ML engineers, software architects, and business stakeholders across industries-from retail and biopharma to automotive and aviation.
Through Dezolva, I help businesses bridge the gap between AI theory and production-ready reality—from custom ML models that unblock operations to independent advisory for NYC-based firms scaling AI for enterprise efficiency. I work end-to-end: from problem framing and exploratory modeling through MLOps, platform architecture, and stakeholder communication. My toolbox includes AWS, GCP, Azure, Kubernetes, and modern ML frameworks, and I'm equally comfortable writing PyTorch models and building the APIs that serve them.
Services
Helping businesses bridge the gap between AI theory and production-ready reality—from discovery and modeling through deployment, monitoring, and iteration.
Designing and deploying tailored machine learning models that solve complex operational bottlenecks, including GenAI, recommendations, and evaluation with safety guardrails.
Guiding leadership teams through the technical and strategic hurdles of scaling AI—platforms on Kubernetes, CD4ML pipelines, and multi-team governance that enhance enterprise efficiency.
Independent, high-impact strategic consulting for NYC-based firms looking to outpace the competition, with full-stack delivery when the work needs to ship.
Selected Work
Built scalable generative AI for product description generation and recommendation systems adopted enterprise-wide. Delivered ~$1M in annual revenue impact, ~$6M in potential savings, and compressed description time-to-market by approximately 3 years. Defined custom evaluation metrics and safety guardrails.
View case study →Partnered with cancer research stakeholders to prioritize drug candidates. Shipped a Bayesian optimization model that cut experimentation time by at least six months. Built a Neo4j knowledge graph linking drugs, cancer cells, and target genes to surface missing relationships and guide drug repurposing.
View case study →Architected an enterprise ML platform on Kubernetes with Kubeflow, enabling 10+ data science teams to run CD4ML pipelines with automated model deployment. Delivered production use cases and drove ~20% reduction in operational overhead. Proposed and implemented a platform extension for GenAI workloads.
View case study →Contributed to a work-shift optimization solution using Google OR-Tools, achieving ~90% reduction in manual schedule creation time and ~5% improvement in workforce utilization.
View case study →Designed and deployed deep learning models to extract rich semantic metadata from images, powering keyword-based search across 500,000+ images. Built an image-parsing microservice serving scene labels, objects, parts, and materials.
View research paper →Skills
ML & AI
Platforms & Infrastructure
Engineering
Practices
Experience
Founder & AI Solutions Architect
Lead Data Scientist - Consultant
Data Scientist & ML Engineer
Full Stack Developer
Full Stack Developer
Chief Executive Officer
Web Developer
Education
Aalto University, Espoo, Finland · 2018–2020
American University of Central Asia (AUCA) / Bard College · 2009–2013