Data Science UA vs Harnham: full comparison for 2026
Quick verdict
Data Science UA (3.8/5) edges ahead of Harnham (3.7/5) overall. Data Science UA is the better choice for companies that want to hire Ukrainian ML engineers directly, with an outstaffing option meanwhile. Harnham is the stronger option for companies hiring permanent data or ML staff in the UK or U.S. through a specialist agency. The right choice depends on your project size, budget, and required tech stack.
Data Science UA vs Harnham: head-to-head summary
| Criterion | Data Science UA | Harnham |
|---|---|---|
| Founded | 2016 | 2006 |
| HQ | Kyiv, Ukraine (legal HQ London) | London, United Kingdom |
| Team size | 50–200 | 100–500 |
| Rating | 3.8 / 5 | 3.7 / 5 |
| Primary differentiator | A large AI community and conference series that feeds its recruiting | Twenty years of recruiting only in data and analytics |
| Pricing model | Recruiting fee per hire; outstaffing billed monthly; rates on request | Placement fee for permanent hires; contractor day or hourly rates; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, SQL, Spark |
| Industries served | Technology, Fintech, Healthcare, Retail, Gaming | Financial services, Retail, Healthcare, Media, Technology |
Data Science UA vs Harnham: overview
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.
Harnham
Harnham has recruited for data and analytics roles since 2006 from London, with offices in the U.S. including New York and San Francisco. It places data engineers, data scientists and ML engineers on contract or permanent terms and runs a graduate training arm, Rockborne. As a recruitment agency, it screens through consultants who specialise in data hiring rather than through practising engineers, and contractors are not managed after placement the way a staffing firm's employees are. That makes it better for permanent hires than for managed augmentation.
Services and capabilities: Data Science UA vs Harnham
| Capability | Data Science UA | Harnham |
|---|---|---|
| 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: Data Science UA vs Harnham
| Framework / platform | Data Science UA | Harnham |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | N/A | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Google Cloud | ✓ | N/A |
| Databricks | N/A | ✓ |
| Kubernetes | N/A | N/A |
Pricing comparison: Data Science UA vs Harnham
| Criterion | Data Science UA | Harnham |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Direct hire, Dedicated engineer, Dedicated team | Direct hire, Contract-to-hire, Freelance contract |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Data Science UA vs Harnham
| Dimension | Data Science UA | Harnham |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Technology, Fintech, Healthcare | Financial services, Retail, Healthcare |
| Best use cases | Hiring a permanent computer-vision engineer in Ukraine, Building an AI R&D centre in Europe for a U.S. product company | Hiring a permanent head of data science in London, Placing a contract data engineer for six months |
| Typical project type | Direct hire | Direct hire |
Data Science UA vs Harnham: pros and cons
| 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 |
| Harnham | |
|---|---|
| + | Long specialist history in data recruiting |
| + | Offices in the UK and several U.S. cities |
| + | Both contract and permanent hiring |
| - | Screening by recruitment consultants, not engineers |
| - | Contractors are not managed after placement |
| - | Headcount estimates vary |
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.
Who should choose Harnham?
A typical fit: hiring a permanent head of data science in London.
Twenty years of recruiting only in data and analytics. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Retail, Healthcare, Media, Technology.
Decision matrix: Data Science UA vs Harnham
| Your situation | Recommended choice |
|---|---|
| You want a working engineer, not a recruiter, to run the technical screen | Neither documents an engineer-led screen; run your own technical interview |
| You need one specialist for a few days a week | Neither advertises part-time experts; ask about reduced hours |
| You need several engineers working as one team | Data Science UA |
| 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: Data Science UA (Not published) vs Harnham (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 | Both; Data Science UA rates higher overall |
Use case fit: Data Science UA vs Harnham
| Use case | Data Science UA fit | Harnham fit | Winner |
|---|---|---|---|
| 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 | Strong | Limited | Data Science UA |
| Hiring a permanent head of data science in London | Strong | Strong | Both equally |
| Placing a contract data engineer for six months | Limited | Strong | Harnham |
Verdict: Data Science UA vs Harnham
Data Science UA (3.8/5) is the stronger overall choice for most AI Engineer Staffing projects. A large AI community and conference series that feeds its recruiting.
Harnham (3.7/5) is worth a look if you need placing a contract data engineer for six months. If your situation matches that, Harnham is a competitive option.
Related comparisons
Data Science UA vs Harnham FAQ
Is Data Science UA better than Harnham?
Data Science UA (3.8/5) scores higher overall, but "better" depends on your use case. Data Science UA's strongest advantage: recruiters specialise in AI and data, so briefs are understood. Harnham's strongest advantage: long specialist history in data recruiting.
How do Data Science UA and Harnham differ in pricing?
Data Science UA uses recruiting fee per hire; outstaffing billed monthly; rates on request pricing. Harnham uses placement fee for permanent hires; contractor day or hourly rates; 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: Data Science UA or Harnham?
Harnham 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 Data Science UA and Harnham?
Data Science UA's primary differentiator is: a large AI community and conference series that feeds its recruiting. Harnham's primary differentiator is: twenty years of recruiting only in data and analytics. They also differ in team size (50–200 vs 100–500), minimum engagement (Not published vs Not published), and primary industries served (Technology, Fintech vs Financial services, Retail).
Verify all details directly with each company before making a decision.