Hire Dedicated Data Science Specialists | ML, AI and Predictive Analytics

Rates typically range from $25 to $50/hr for hourly engagements, $1,200 to $2,500/month for fractional (part-time) data scientists, and $3,500 to $6,000/month for full-time dedicated specialists. Get in touch for a custom quote based on your stack and project scope.

A fractional data scientist is a senior specialist engaged on a part-time basis, typically 10 to 20 hours per week. It gives growing companies access to expert analytics capability without the cost of a full-time hire. This model works well for companies with 1 to 3 ongoing analytics projects.

Data science covers the full process of extracting insight from data, including analysis, visualisation, statistics, and ML model development. Machine learning is a subset of data science focused specifically on building systems that learn from data to make predictions or decisions automatically.

Yes. Our specialists are experienced across major cloud platforms (AWS, GCP, Azure), data warehouses (Snowflake, BigQuery, Redshift), BI tools (Tableau, Power BI), and orchestration frameworks (Airflow, dbt). We adapt to your stack.

External hiring works best for organisations with 1 to 9 active data science projects, early-stage analytics programmes, or specific ML use cases. Building in-house makes more sense when data science is a core product function with 10+ concurrent projects at enterprise scale.

All engagements follow ISO 27001 information security protocols, signed NDAs, role-based data access controls, secure development environments, and GDPR-compliant data handling for UK and EU clients.

Depending on scope and system access requirements, onboarding takes 5 to 7 business days from project brief to active development, which is significantly faster than in-house hiring timelines of 3 to 6 months.

Yes. Computyne offers project-based engagements for specific model builds, including churn prediction, demand forecasting, fraud detection, and NLP pipelines, all with full documentation and handover.

Yes. We offer discovery sessions and scoped proof-of-concept engagements so you can validate data science output and team quality before scaling to a longer-term partnership.