SciForce vs Harnham: full comparison for 2026
Quick verdict
SciForce (4.0/5) edges ahead of Harnham (3.7/5) overall. SciForce is the better choice for healthcare data teams that need NLP or data scientists familiar with medical data standards. 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.
SciForce vs Harnham: head-to-head summary
| Criterion | SciForce | Harnham |
|---|---|---|
| Founded | 2015 | 2006 |
| HQ | Lviv, Ukraine (office in Tallinn, Estonia) | London, United Kingdom |
| Team size | 50–99 | 100–500 |
| Rating | 4.0 / 5 | 3.7 / 5 |
| Primary differentiator | Medical data science experience plus a documented multi-year placement engagement | Twenty years of recruiting only in data and analytics |
| Pricing model | Dedicated team billed monthly; projects quoted separately; 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 | Healthcare, Financial services, Logistics, Agriculture, Education | Financial services, Retail, Healthcare, Media, Technology |
SciForce vs Harnham: overview
SciForce
SciForce has worked on AI and data science since 2015, with R&D offices in Lviv and Kharkiv and a representative office in Tallinn. Directories list 50 to 99 people. The clearest evidence of its staffing work is a Clutch review from a financial services IT director describing an engagement from January 2019 to February 2023 in which SciForce sourced and placed engineering talent and supplied a team of six to ten. Medical data science is a notable specialty, alongside NLP and logistics AI.
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: SciForce vs Harnham
| Capability | SciForce | 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: SciForce vs Harnham
| Framework / platform | SciForce | Harnham |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | N/A | N/A |
| Hugging Face | ✓ | N/A |
| OpenAI | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Google Cloud | N/A | N/A |
| Databricks | N/A | ✓ |
| Kubernetes | N/A | N/A |
Pricing comparison: SciForce vs Harnham
| Criterion | SciForce | Harnham |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Dedicated engineer, Dedicated team, Project delivery | Direct hire, Contract-to-hire, Freelance contract |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: SciForce vs Harnham
| Dimension | SciForce | Harnham |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Healthcare, Financial services, Logistics | Financial services, Retail, Healthcare |
| Best use cases | Adding an NLP engineer for clinical text extraction, Staffing a six-person data team for a financial client | Hiring a permanent head of data science in London, Placing a contract data engineer for six months |
| Typical project type | Dedicated engineer | Direct hire |
SciForce vs Harnham: pros and cons
| SciForce | |
|---|---|
| + | A four-year augmentation engagement rated 5.0 on Clutch |
| + | Medical NLP and healthcare data experience |
| + | Lower cost base than Western European suppliers |
| - | Small team, with only a few engineers free at any time |
| - | Most staffing evidence comes from a single review |
| - | Wartime conditions in Ukraine 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 SciForce?
A typical fit: adding an NLP engineer for clinical text extraction.
Medical data science experience plus a documented multi-year placement engagement. Minimum engagement is not publicly disclosed. Works best with clients in Healthcare, Financial services, Logistics, Agriculture, Education.
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: SciForce 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 | SciForce |
| 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: SciForce (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 | Harnham |
Use case fit: SciForce vs Harnham
| Use case | SciForce fit | Harnham fit | Winner |
|---|---|---|---|
| Adding an NLP engineer for clinical text extraction | Strong | Limited | SciForce |
| Staffing a six-person data team for a financial client | Strong | Limited | SciForce |
| Hiring a permanent head of data science in London | Limited | Strong | Harnham |
| Placing a contract data engineer for six months | Limited | Strong | Harnham |
Verdict: SciForce vs Harnham
SciForce (4.0/5) is the stronger overall choice for most AI Engineer Staffing projects. Medical data science experience plus a documented multi-year placement engagement.
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
SciForce vs Harnham FAQ
Is SciForce better than Harnham?
SciForce (4.0/5) scores higher overall, but "better" depends on your use case. SciForce's strongest advantage: a four-year augmentation engagement rated 5.0 on Clutch. Harnham's strongest advantage: long specialist history in data recruiting.
How do SciForce and Harnham differ in pricing?
SciForce uses dedicated team billed monthly; projects quoted separately; 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: SciForce 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 SciForce and Harnham?
SciForce's primary differentiator is: medical data science experience plus a documented multi-year placement engagement. Harnham's primary differentiator is: twenty years of recruiting only in data and analytics. They also differ in team size (50–99 vs 100–500), minimum engagement (Not published vs Not published), and primary industries served (Healthcare, Financial services vs Financial services, Retail).
Verify all details directly with each company before making a decision.