Kostya Kavaleuski

Kostya Kavaleuski is a healthcare IT & AI consultant specializing in life sciences software. With a background in biochemistry and postgraduate training in bioinformatics, he helps turn scientific workflows and data needs into clear software requirements.

Kostya began his IT career supporting a laboratory information management system used by pharmaceutical companies, contract research organizations, and research laboratories. This work introduced him to laboratory operations and software used in environments subject to GxP requirements and FDA 21 CFR Part 11.

He also worked in enterprise application support, where he led a team of five support engineers, investigated production issues, addressed the root causes of recurring problems, and coordinated software evolution with developers. Under Kostya’s leadership, the team increased its customer satisfaction score by 16% and reduced response and resolution times by 20%. This experience gave him a practical understanding of how software requirements and design decisions affect users after a system goes live.

Kostya’s experience resolving production issues and interest in how software design shapes future user satisfaction led Kostya to pursue business analysis. As an embedded business analyst on a project team, he handled the full business analysis lifecycle, including requirements elicitation, process modeling, functional specifications, user acceptance testing, training, and post-release support.

As ScienceSoft expanded its healthcare IT practice, Kostya took on the role of healthcare IT & AI consultant, applying his scientific background, regulated laboratory software experience, and business analysis skills to life sciences and biotechnology initiatives.

In his current role, Kostya helps clients accurately describe scientific workflows, define software requirements, and determine the scope of new software initiatives. He contributes to presales and discovery projects, while building deeper expertise in software for genetics, molecular biology, and biotechnology. Most recently, he led the discovery phase for a life sciences data analysis platform, taking responsibility for requirements gathering, scope definition, and the final discovery deliverable.

In life sciences software, workflow requirements need to reflect how scientific data is generated, reviewed, and validated. If that logic is lost in translation, the resulting system may be technically sound but unsuitable for real laboratory or research work.