Proxify vs Data Science UA: full comparison for 2026
Quick verdict
Proxify (4.4/5) edges ahead of Data Science UA (3.8/5) overall. Proxify is the better choice for european companies that want a vetted ML or data engineer on European working hours. Data Science UA is the stronger option for companies that want to hire Ukrainian ML engineers directly, with an outstaffing option meanwhile. The right choice depends on your project size, budget, and required tech stack.
Proxify vs Data Science UA: head-to-head summary
| Criterion | Proxify | Data Science UA |
|---|---|---|
| Founded | 2018 | 2016 |
| HQ | Stockholm, Sweden | Kyiv, Ukraine (legal HQ London) |
| Team size | 5,000+ network members | 50–200 |
| Rating | 4.4 / 5 | 3.8 / 5 |
| Primary differentiator | Senior-engineer interviews with live coding after an automated skills test | A large AI community and conference series that feeds its recruiting |
| Pricing model | Hourly rate per developer billed monthly; full-time or part-time; rates on request | Recruiting fee per hire; outstaffing billed monthly; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, PyTorch, TensorFlow |
| Industries served | SaaS, Fintech, E-commerce, Media, Healthcare | Technology, Fintech, Healthcare, Retail, Gaming |
Proxify vs Data Science UA: overview
Proxify
Proxify was founded in Stockholm in 2018 (one of its own pages says 2019) and matches companies with vetted developers across web, data, AI and DevOps. Candidates take Codility-based skills tests, then sit in-depth technical interviews with Proxify's senior engineers that include live coding and practical problems. The company quotes an acceptance rate of 1–3%, though the figure varies from page to page. Its network covers more than 5,000 professionals in over 90 countries, and it appeared on the Financial Times 1,000 list in 2025. Matching uses in-house AI tools alongside its hiring team.
Data Science UA
Data Science UA began in 2016 as a data science conference in Kyiv, founded by Aleksandra Boguslavskaya, and grew into a recruiting, outstaffing and AI consulting business. Recruiting is a core line, and it says hiring averages two to four weeks. Its community of AI engineers in Ukraine and beyond, quoted at 10,000 to 30,000 depending on the source, gives it reach that general agencies lack. The screening is recruiter-led, though, so the technical depth of each shortlist depends on how well you brief them and on your own interviews.
Services and capabilities: Proxify vs Data Science UA
| Capability | Proxify | Data Science UA |
|---|---|---|
| ML engineers | ✓ | ✓ |
| LLM / GenAI engineers | ✓ | ✗ |
| AI agent developers | ✗ | ✗ |
| MLOps engineers | ✗ | ✗ |
| Computer vision engineers | ✗ | ✓ |
| NLP engineers | ✗ | ✗ |
| Data engineers | ✓ | ✓ |
| Engineer-led technical screen | ✓ | ✗ |
| Fractional / part-time experts | ✓ | ✗ |
| Trial before commitment | ✗ | ✗ |
| Nearshore time-zone overlap | ✗ | ✗ |
| Direct hire option | ✗ | ✓ |
Tech stack comparison: Proxify vs Data Science UA
| Framework / platform | Proxify | Data Science UA |
|---|---|---|
| PyTorch | ✓ | ✓ |
| TensorFlow | ✓ | ✓ |
| LangChain | N/A | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Google Cloud | ✓ | ✓ |
| Databricks | ✓ | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: Proxify vs Data Science UA
| Criterion | Proxify | Data Science UA |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Dedicated engineer, Fractional expert, Freelance contract | Direct hire, Dedicated engineer, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Proxify vs Data Science UA
| Dimension | Proxify | Data Science UA |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | SaaS, Fintech, E-commerce | Technology, Fintech, Healthcare |
| Best use cases | Adding a data engineer to a European fintech's analytics team, Hiring a Python ML developer for a recommender system | Hiring a permanent computer-vision engineer in Ukraine, Building an AI R&D centre in Europe for a U.S. product company |
| Typical project type | Dedicated engineer | Direct hire |
Proxify vs Data Science UA: pros and cons
| Proxify | |
|---|---|
| + | Live-coding interviews with in-house senior engineers are part of the published process |
| + | Most of the network is in European time zones, which suits teams in the EU and UK |
| + | Grew fast enough to make the Financial Times 1,000 list in 2025 |
| - | AI is one of many skill areas, and there is no AI-specific test on the record |
| - | Acceptance-rate and network-size figures differ across the company's own pages |
| - | Developers are contractors on the platform, not Proxify employees |
| Data Science UA | |
|---|---|
| + | Recruiters specialise in AI and data, so briefs are understood |
| + | Direct hire and outstaffing both available |
| + | Wide reach in the Ukrainian AI community |
| - | Screening is done by recruiters, not engineers |
| - | Size and headquarters differ across directories |
| - | Wartime conditions need a continuity plan |
Who should choose Proxify?
A typical fit: adding a data engineer to a European fintech's analytics team.
Senior-engineer interviews with live coding after an automated skills test. Minimum engagement is not publicly disclosed. Works best with clients in SaaS, Fintech, E-commerce, Media, Healthcare.
Who should choose Data Science UA?
A typical fit: hiring a permanent computer-vision engineer in Ukraine.
A large AI community and conference series that feeds its recruiting. Minimum engagement is not publicly disclosed. Works best with clients in Technology, Fintech, Healthcare, Retail, Gaming.
Decision matrix: Proxify vs Data Science UA
| Your situation | Recommended choice |
|---|---|
| You want a working engineer, not a recruiter, to run the technical screen | Proxify |
| You need one specialist for a few days a week | Proxify |
| You need several engineers working as one team | Both; Proxify rates higher overall |
| You want to test an engineer before committing | Neither publishes a trial; negotiate a short first term |
| Your budget is at the lower end | Compare: Proxify (Not published) vs Data Science UA (Not published) |
| Your team works U.S. hours | Neither lists Latin American engineers; confirm overlap hours in the contract |
| You may want to hire the engineer permanently later | Data Science UA |
Use case fit: Proxify vs Data Science UA
| Use case | Proxify fit | Data Science UA fit | Winner |
|---|---|---|---|
| Adding a data engineer to a European fintech's analytics team | Strong | Limited | Proxify |
| Hiring a Python ML developer for a recommender system | Strong | Strong | Both equally |
| Hiring a permanent computer-vision engineer in Ukraine | Strong | Strong | Both equally |
| Building an AI R&D centre in Europe for a U.S. product company | Limited | Strong | Data Science UA |
Verdict: Proxify vs Data Science UA
Proxify (4.4/5) is the stronger overall choice for most AI Engineer Staffing projects. Senior-engineer interviews with live coding after an automated skills test.
Data Science UA (3.8/5) is worth a look if you need building an AI R&D centre in Europe for a U.S. product company. If your situation matches that, Data Science UA is a competitive option.
Related comparisons
Proxify vs Data Science UA FAQ
Is Proxify better than Data Science UA?
Proxify (4.4/5) scores higher overall, but "better" depends on your use case. Proxify's strongest advantage: live-coding interviews with in-house senior engineers are part of the published process. Data Science UA's strongest advantage: recruiters specialise in AI and data, so briefs are understood.
How do Proxify and Data Science UA differ in pricing?
Proxify uses hourly rate per developer billed monthly; full-time or part-time; rates on request pricing. Data Science UA uses recruiting fee per hire; outstaffing billed monthly; rates on request pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Proxify or Data Science UA?
Data Science UA is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each company before shortlisting.
What are the main differences between Proxify and Data Science UA?
Proxify's primary differentiator is: senior-engineer interviews with live coding after an automated skills test. Data Science UA's primary differentiator is: a large AI community and conference series that feeds its recruiting. They also differ in team size (5,000+ network members vs 50–200), minimum engagement (Not published vs Not published), and primary industries served (SaaS, Fintech vs Technology, Fintech).
Verify all details directly with each company before making a decision.