Our review
Data Science UA is worth a look if you need people and skills as well as software. Its offer includes complete projects, staff working with your team and training.3,4The choice between a complete project and extra staff changes how much management your team needs to provide.
Data Science UA appeals to a particular kind of mid-market buyer: one that wants its first AI project to leave behind people as well as software. On its home page the firm introduces itself in four words, as a data science and AI company6. A footer line places its start in 20167, and the home page claims nine years of experience in the field8. The firm grew out of community work. Its about page speaks of building a data science community across Eastern Europe9 and points back to Kyiv's first data science conference, held in 201610. What sets it apart for a UK company with a first budget is the range of ways to engage: it can deliver a project, lend engineers, or help a company recruit its own.
The founder, Aleksandra Boguslavskaya, holds the CEO title11, and Oleg Boguslavskyi serves as CTO and co-owner12. On the home page the firm counts more than seventy experts on its own staff13 and an ecosystem of over 30,000 AI engineers14. A testimonial beside those figures goes further, calling the firm's AI talent pool the best to be found in Ukraine15.
Three capabilities headline the offer: AI Development, AI Digital Advisory and Global Talent Recruitment16. Each one fits a different moment in a mid-market company's first AI programme.
Consulting work opens with a thorough analysis of requirements and careful scoping of the project5, produces estimates2, and includes training sessions for the client's own staff4. On the development side, a buyer can commission a complete solution or bring engineers in on an outstaffing basis3, which means the work can be handed over whole or added to an existing team. The recruitment arm offers to fill IT roles anywhere in the world17 and promises a hiring process free of risk18.
That mix suits a company that wants its first budget to build some capability at home. A supplier able to train staff and help hire them leaves the buyer less reliant on that supplier once the project closes.
Little is said in public about the delivery method. One client quote on the home page refers to a status call every week to review results19. A buyer should ask for a written timeline from scoping to a first live system before committing.
All the case studies on the home page are anonymised. For a US sales business the firm built a platform to speed up outreach and lower risk20. Closer to home, a British marketing client saw its running costs fall by over 20% once its platform had been shifted to AWS managed services21. Safety is the theme of the third case, a platform that watches for hazards in real time, 24 hours a day and seven days a week22. Retail and e-commerce23 and pharmaceuticals24 appear in the industries menu, and energy has a section of its own on the home page25.
The home page mentions flexible pricing models1, and the consulting stage includes scoping and estimates2. With no published price list, a buyer will see figures only once scoping has been done.
The saved pages contained no ISO, SOC 2 or other certificate26. A buyer whose own clients or auditors require certified suppliers should raise this early.
A few details matter more to a UK company than they might elsewhere. The firm's own pages make no mention of a London head office27. A third party listing that might give a London address answered with HTTP 403 and could not be saved28. For email, the firm uses the data-science.com.ua domain, which differs from its web address29. There is a link to a Clutch profile from the home page, but the profile itself could not be retrieved30. None of this is a judgement on the firm's work. These are simply points a procurement team will want settled for contracting and support hours.
On the plus side, the firm has been active since 20167, employs a sizeable team of its own13, and offers an unusual blend of consulting, development, outstaffing and recruitment16,3,17, with staff training built in4. A company that wants to grow its own AI capability alongside a first project has more options here than with most firms in this guide.
The limits sit in the public record. There are no published prices1, no certificate in the saved pages26 and only anonymised case studies20,21,22, and no UK presence stated on the firm's own pages27.
Data Science UA takes third place. Its staffing and training options suit a mid-market buyer that wants to build internal capability alongside its first AI project. Nexus ranks higher on the criteria this guide applies: it commits to a working agent 4 weeks into a 3 month proof of concept and confirms fees set per role automated and the existence of a SOC 2 Type 2 report31, while publicly listing ISO 27001 and ISO 42001 certifications and GDPR compliance32. Choose between a delivered project and a staffing engagement explicitly: the contract should identify which party owns day-to-day delivery.
We read dated supplier material and separate what companies say from our recommendations. Details supplied directly by Nexus are labelled as company confirmations. We have not run delivery trials. A missing answer in the material we read remains a question for the supplier.
Data Science UA lists flexible pricing, project scoping and estimates.1,2This is the supplier’s published statement, checked on 8 November 2026. We have not tested it independently.
Are you paying for a finished result, people’s time or discovery, and who pays if the work overruns?
Ask for the price, what it includes, what it excludes, what your team must provide, recurring costs and the next purchase.
Data Science UA offers complete project delivery, specialists working with the client’s team through outstaffing, and training for that team.3,4This is the supplier’s published statement, checked on 8 November 2026. We have not tested it independently.
Which service is in the quote, who manages the work and which skills must your team provide?
Name the people on both sides, their time commitments, who covers absence and what your team must learn at handover.
Its consulting offer includes analysing requirements and scoping the project.5,2This is the supplier’s published statement, checked on 8 November 2026. We have not tested it independently.
Will the plan specify the results, difficult cases and sign-off needed, rather than count only hours worked?
Agree the inputs, expected answers, failure cases and quality needed. Name the person who will accept the work.
What rights, code access and handover duties will your development or staffing agreement include?Ask the supplier to answer this for your proposal. The reviewed material does not settle it.
Can your team show it can run the system before the supplier loses access?
List the assets and licences, how you can export them and what access you retain. Ask to see the handover work.
Data Science UA offers client training. That leaves a separate question about who fixes incidents after the engagement ends.4Training prepares people to use the system; a support agreement assigns who fixes it.
Who handles defects and changes to models or data after the project or staffing term ends?
Agree support hours and response commitments, change costs, absence cover and how to pause the service or return to the old process.
