Globant vs Data Science UA: full comparison for 2026
Quick verdict
Globant (4.1/5) edges ahead of Data Science UA (3.8/5) overall. Globant is the better choice for enterprises that want to buy AI delivery as a subscription instead of paying for hours. Data Science UA is the stronger option for companies that want to choose between a recruiting fee and monthly outstaffing for Ukrainian AI talent. The right choice depends on your project size, budget, and required tech stack.
Globant vs Data Science UA: head-to-head summary
| Criterion | Globant | Data Science UA |
|---|---|---|
| Founded | 2003 | 2016 |
| HQ | Luxembourg (founded in Buenos Aires, Argentina) | Kyiv, Ukraine (legal HQ London) |
| Team size | 27,000+ | 50–200 |
| Rating | 4.1 / 5 | 3.8 / 5 |
| Primary differentiator | Token-metered AI Pods subscription alongside conventional staffing | Recruiting fee or monthly outstaffing from an AI-only recruiter |
| Pricing model | AI Pods subscription with token-based capacity; conventional teams billed monthly; rates on request | Recruiting fee per hire; outstaffing billed monthly; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, OpenAI, Google Cloud | Python, PyTorch, TensorFlow |
| Industries served | Media, Financial services, Retail, Travel, Healthcare | Technology, Fintech, Healthcare, Retail, Gaming |
Globant vs Data Science UA: overview
Globant
Globant was founded in 2003 in Buenos Aires and had about 27,400 employees in mid-2026 after cutting from roughly 30,000. It is here because of how its newest service is bought. AI Pods are agent-driven service units supervised by Globant experts and sold as a subscription with token-based capacity, so you pay for output rather than for engineers' hours. AI Pod annual recurring revenue reached $52.8 million in June 2026, still around 2% of company revenue. Classic staff augmentation remains available, but this is a large generalist, not an AI specialist.
Data Science UA
Data Science UA grew out of a 2016 data science conference in Kyiv and now runs recruiting, outstaffing and AI consulting, with a legal base in London. It offers two ways to buy. You can pay a recruiting fee for a permanent hire, which it says takes two to four weeks on average, or take the engineer on monthly outstaffing terms first. Its AI community, quoted at 10,000 to 30,000 people, gives it reach. Screening is done by recruiters, so plan your own technical interview.
Services and capabilities: Globant vs Data Science UA
| Capability | Globant | Data Science UA |
|---|---|---|
| Full-time dedicated engineers | ✗ | ✓ |
| Part-time / fractional experts | ✗ | ✗ |
| Dedicated team | ✓ | ✓ |
| Trial before commitment | ✗ | ✗ |
| Published rates | ✗ | ✗ |
| Direct hire option | ✗ | ✓ |
| Subscription or output-based pricing | ✓ | ✗ |
| Nearshore time-zone overlap | ✓ | ✗ |
| LLM / GenAI engineers | ✓ | ✗ |
| MLOps | ✗ | ✗ |
| Computer vision | ✗ | ✓ |
| Data engineering | ✓ | ✗ |
Tech stack comparison: Globant vs Data Science UA
| Framework / platform | Globant | Data Science UA |
|---|---|---|
| PyTorch | N/A | ✓ |
| TensorFlow | N/A | ✓ |
| LangChain | N/A | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Google Cloud | ✓ | N/A |
| Databricks | ✓ | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: Globant vs Data Science UA
| Criterion | Globant | Data Science UA |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Subscription, Dedicated team, Project delivery | Direct hire, Full-time dedicated, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Globant vs Data Science UA
| Dimension | Globant | Data Science UA |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Media, Financial services, Retail | Technology, Fintech, Healthcare |
| Best use cases | Testing a subscription model for internal software maintenance, Buying agent-driven QA capacity by the token | Hiring a permanent ML engineer in Ukraine, Outstaffing a computer vision engineer before a permanent offer |
| Typical project type | Subscription | Direct hire |
Globant vs Data Science UA: pros and cons
| Globant | |
|---|---|
| + | A genuinely different way to buy: output capacity, not headcount |
| + | Large Latin American workforce on U.S.-friendly hours |
| + | Publicly listed, with audited reporting on the AI Pods business |
| - | AI Pods are new and only about 2% of revenue |
| - | A generalist where AI is one line among many |
| - | Recent layoffs and a cut to annual guidance in 2026 |
| Data Science UA | |
|---|---|
| + | Both recruiting and outstaffing |
| + | Recruiters focused on AI roles |
| + | Large Ukrainian AI community |
| - | Recruiter-led screening |
| - | Size and headquarters vary by source |
| - | Wartime continuity risk |
Who should choose Globant?
A typical fit: testing a subscription model for internal software maintenance.
Token-metered AI Pods subscription alongside conventional staffing. Minimum engagement is not publicly disclosed. Works best with clients in Media, Financial services, Retail, Travel, Healthcare.
Who should choose Data Science UA?
A typical fit: hiring a permanent ML engineer in Ukraine.
Recruiting fee or monthly outstaffing from an AI-only recruiter. Minimum engagement is not publicly disclosed. Works best with clients in Technology, Fintech, Healthcare, Retail, Gaming.
Decision matrix: Globant vs Data Science UA
| Your situation | Recommended choice |
|---|---|
| You want one engineer full-time on a monthly contract | Data Science UA |
| You only need a specialist a few days a week | Neither advertises part-time experts; ask about reduced hours |
| You want to test an engineer before committing | Neither publishes a trial; negotiate a short first term |
| You need a rate before the first call | Neither publishes rates; ask both for a written rate card |
| Your budget is at the lower end | Compare: Globant (Not published) vs Data Science UA (Not published) |
| You may want to hire the engineer permanently later | Data Science UA |
| You want several engineers working as one team | Both; Globant rates higher overall |
Use case fit: Globant vs Data Science UA
| Use case | Globant fit | Data Science UA fit | Winner |
|---|---|---|---|
| Testing a subscription model for internal software maintenance | Strong | Limited | Globant |
| Buying agent-driven QA capacity by the token | Strong | Limited | Globant |
| Hiring a permanent ML engineer in Ukraine | Limited | Strong | Data Science UA |
| Outstaffing a computer vision engineer before a permanent offer | Limited | Strong | Data Science UA |
Verdict: Globant vs Data Science UA
Globant (4.1/5) is the stronger overall choice for most AI Staff Augmentation projects. Token-metered AI Pods subscription alongside conventional staffing.
Data Science UA (3.8/5) is worth a look if you need outstaffing a computer vision engineer before a permanent offer. If your situation matches that, Data Science UA is a competitive option.
Related comparisons
Globant vs Data Science UA FAQ
Is Globant better than Data Science UA?
Globant (4.1/5) scores higher overall, but "better" depends on your use case. Globant's strongest advantage: a genuinely different way to buy: output capacity, not headcount. Data Science UA's strongest advantage: both recruiting and outstaffing.
How do Globant and Data Science UA differ in pricing?
Globant uses ai pods subscription with token-based capacity; conventional teams billed monthly; 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: Globant 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 provider before shortlisting.
What are the main differences between Globant and Data Science UA?
Globant's primary differentiator is: token-metered AI Pods subscription alongside conventional staffing. Data Science UA's primary differentiator is: recruiting fee or monthly outstaffing from an AI-only recruiter. They also differ in team size (27,000+ vs 50–200), minimum engagement (Not published vs Not published), and primary industries served (Media, Financial services vs Technology, Fintech).
Verify all details directly with each provider before making a decision.