Howdy.com vs ScienceSoft: full comparison for 2026
Quick verdict
Howdy.com (4.1/5) edges ahead of ScienceSoft (4.0/5) overall. Howdy.com is the better choice for teams that want transparent nearshore pricing. ScienceSoft is the stronger option for regulated industries hiring experienced data scientists. The right choice depends on your project size, budget, and required tech stack.
Howdy.com vs ScienceSoft: head-to-head summary
| Criterion | Howdy.com | ScienceSoft |
|---|---|---|
| Founded | 2018 | 1989 |
| HQ | Austin, Texas, USA | McKinney, Texas, USA |
| Team size | 100–249 | 750+ |
| Rating | 4.1 / 5 | 4.0 / 5 |
| Primary differentiator | Published 15% fee on top of the engineer's pay | Senior data scientists with a published hiring timeline |
| Pricing model | Engineer salary plus a flat 15% service fee (published) | Time and materials; rates sent with CVs |
| Min. engagement | 1 engineer | Not disclosed |
| Primary tech stack | Python, AWS, Databricks | Python, R, Azure ML |
| Industries served | SaaS, Fintech, Healthcare, E-commerce | Healthcare, Manufacturing, Fintech, Retail |
Howdy.com vs ScienceSoft: overview
Howdy.com
Howdy.com was founded in Austin, Texas, in 2018 by Jacqueline Samira, with Frank Licea later joining as co-founder and CTO. Unlike a pure marketplace, it recruits, employs and supports its engineers, and it runs in-country hubs it calls Howdy Houses in Latin American cities. In August 2023 it acquired the Brazilian talent marketplace GeekHunter, citing rising demand for AI and ML skills. A 2026 industry ranking lists its fee as a flat 15% of the billed rate.
ScienceSoft
ScienceSoft dates its IT work to 1989 and is headquartered in McKinney, Texas, with representative offices in the UAE, Saudi Arabia, Europe and Mexico. Its staff-augmentation pool covers more than 750 professionals, including data scientists with 7–20 years of experience. The company says it sends CVs with rates within 24 hours, arranges interviews in two to four days and has people starting within one to two weeks (per company website; independently unverifiable).
Services and capabilities: Howdy.com vs ScienceSoft
| Capability | Howdy.com | ScienceSoft |
|---|---|---|
| LLM / GenAI engineers | ✗ | ✗ |
| MLOps & deployment | ✗ | ✗ |
| Computer vision | ✗ | ✗ |
| Data engineering | ✓ | ✓ |
| AI agent development | ✗ | ✗ |
| Fractional / part-time experts | ✗ | ✗ |
| Risk-free trial period | ✗ | ✗ |
| Nearshore time-zone overlap | ✓ | ✗ |
Tech stack comparison: Howdy.com vs ScienceSoft
| Framework / platform | Howdy.com | ScienceSoft |
|---|---|---|
| PyTorch | N/A | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | N/A | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | N/A | N/A |
| AWS SageMaker | N/A | ✓ |
| Azure ML | N/A | ✓ |
| Databricks | ✓ | N/A |
| MLflow | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: Howdy.com vs ScienceSoft
| Criterion | Howdy.com | ScienceSoft |
|---|---|---|
| Minimum engagement | 1 engineer | Not disclosed |
| Engagement models | Full-time dedicated engineers, Dedicated team | Full-time dedicated engineers, Dedicated team, Managed delivery |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Accessible | Mid-market |
Target audience comparison: Howdy.com vs ScienceSoft
| Dimension | Howdy.com | ScienceSoft |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | SaaS, Fintech, Healthcare | Healthcare, Manufacturing, Fintech |
| Best use cases | Hiring a full-time LatAm data engineer with clear cost visibility, Building a two-to-four person nearshore team for a U.S. startup | Adding a senior data scientist to a healthcare analytics team, Staffing a manufacturing predictive-maintenance project |
| Typical project type | Full-time dedicated engineers | Full-time dedicated engineers |
Howdy.com vs ScienceSoft: pros and cons
| Howdy.com | |
|---|---|
| + | Fee structure is published, so you can see what the engineer actually earns |
| + | Engineers are employed and supported locally, which helps retention |
| + | GeekHunter acquisition widened its Brazilian candidate pool |
| + | U.S. time zones |
| - | AI depth depends on who is available; it is a general engineering staffing company |
| - | Disclosure: acquired GeekHunter in 2023, so part of its candidate supply comes through a marketplace subsidiary |
| - | Technical screening is lighter than at AI-only companies |
| ScienceSoft | |
|---|---|
| + | Rates arrive with the CVs, before any sales calls |
| + | Long history in healthcare and manufacturing IT |
| + | Experienced data scientists rather than junior ML hires |
| - | AI is one of many service lines |
| - | Smaller bench than the large nearshore firms |
| - | Headcount figures differ between the company's own pages |
Who should choose Howdy.com?
A typical fit: hiring a full-time LatAm data engineer with clear cost visibility.
Published 15% fee on top of the engineer's pay. Minimum engagement starts at 1 engineer. Works best with clients in SaaS, Fintech, Healthcare, E-commerce.
Who should choose ScienceSoft?
A typical fit: adding a senior data scientist to a healthcare analytics team.
Senior data scientists with a published hiring timeline. Minimum engagement is not publicly disclosed. Works best with clients in Healthcare, Manufacturing, Fintech, Retail.
Decision matrix: Howdy.com vs ScienceSoft
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Both offer fixed-price models |
| You need a large dedicated team for an ongoing programme | Howdy.com |
| Your budget is at the lower end | Compare: Howdy.com (1 engineer) vs ScienceSoft (Not disclosed) |
| You need specialist depth in a specific vertical | Howdy.com |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Both may offer discovery engagements |
Use case fit: Howdy.com vs ScienceSoft
| Use case | Howdy.com fit | ScienceSoft fit | Winner |
|---|---|---|---|
| Hiring a full-time LatAm data engineer with clear cost visibility | Strong | Limited | Howdy.com |
| Building a two-to-four person nearshore team for a U.S. startup | Strong | Limited | Howdy.com |
| Adding a senior data scientist to a healthcare analytics team | Strong | Strong | Both equally |
| Staffing a manufacturing predictive-maintenance project | Limited | Strong | ScienceSoft |
Verdict: Howdy.com vs ScienceSoft
Howdy.com (4.1/5) is the stronger overall choice for most AI Staffing projects. Published 15% fee on top of the engineer's pay.
ScienceSoft (4.0/5) is worth a look if you need staffing a manufacturing predictive-maintenance project. If your situation matches that, ScienceSoft is a competitive option.
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Howdy.com vs ScienceSoft FAQ
Is Howdy.com better than ScienceSoft?
Howdy.com (4.1/5) scores higher overall, but "better" depends on your use case. Howdy.com's strongest advantage: fee structure is published, so you can see what the engineer actually earns. ScienceSoft's strongest advantage: rates arrive with the CVs, before any sales calls.
How do Howdy.com and ScienceSoft differ in pricing?
Howdy.com uses engineer salary plus a flat 15% service fee (published) pricing with a minimum engagement of 1 engineer. ScienceSoft uses time and materials; rates sent with cvs pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Howdy.com or ScienceSoft?
Howdy.com is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each agency before shortlisting.
What are the main differences between Howdy.com and ScienceSoft?
Howdy.com's primary differentiator is: published 15% fee on top of the engineer's pay. ScienceSoft's primary differentiator is: senior data scientists with a published hiring timeline. They also differ in team size (100–249 vs 750+), minimum engagement (1 engineer vs Not disclosed), and primary industries served (SaaS, Fintech vs Healthcare, Manufacturing).
Verify all details directly with each agency before making a decision.