What is the difference between a data scientist and ML engineer?

Data scientists focus on analysis, modeling, and insights. ML engineers focus on deploying and scaling models in production systems.

Do they work with business stakeholders?

Yes. Our data scientists translate business questions into analytical frameworks and communicate findings to non-technical stakeholders.

What tools do they use?

Our data scientists work with Python, Jupyter notebooks, scikit-learn, TensorFlow, and visualization tools like Plotly and Tableau.

Hire a Data Scientist

Get a pre-vetted data scientist for statistical modeling, predictive analytics, and actionable insights — delivered with AI-managed precision.

Role: Data Scientist (Data)

Data scientists extract insights and build predictive models from complex datasets. Our vetted data science talent delivers exploratory analysis, statistical modeling, A/B testing frameworks, and machine learning solutions that drive business decisions.

Skills We Vet

Statistical Modeling & Hypothesis Testing: Expert
Python (scikit-learn, Pandas): Expert
Machine Learning Algorithms: Advanced
Data Visualization (Matplotlib, Plotly): Advanced

Typical Projects

Predictive Model: Customer churn, demand forecasting, or risk scoring model with feature engineering and validation. (60-140 hrs)
A/B Testing Framework: Statistical experimentation platform with power analysis, significance testing, and automated reporting. (40-80 hrs)
Data Analysis & Dashboard: Exploratory data analysis with interactive visualizations and executive summary reports. (30-60 hrs)

Hourly Rates

AI PM: $2/hr — AI agent manages the project end-to-end with automated code reviews, testing, and deployment.
Live PM: $3/hr — A human project manager coordinates your project with AI-augmented development workflows.
Live PM + Dev: $5/hr — Dedicated human PM plus senior developer oversight for mission-critical projects.

Hiring Process

Submit Your Requirements: Describe your project scope, technical needs, and timeline. Our AI analyzes your requirements and identifies the ideal skill profile.
AI-Matched Talent Selection: Our platform matches you with pre-vetted developers whose expertise aligns with your tech stack, industry, and project complexity.
Technical Vetting & Trial: Review candidate profiles, past work, and skill assessments. Start with a small paid trial task to validate the fit before committing.
Kick-off & Ongoing Delivery: Once confirmed, your developer is onboarded immediately. Track progress via real-time dashboards, milestone reviews, and daily stand-ups.

Frequently Asked Questions

What is the difference between a data scientist and ML engineer?: Data scientists focus on analysis, modeling, and insights. ML engineers focus on deploying and scaling models in production systems.
Do they work with business stakeholders?: Yes. Our data scientists translate business questions into analytical frameworks and communicate findings to non-technical stakeholders.
What tools do they use?: Our data scientists work with Python, Jupyter notebooks, scikit-learn, TensorFlow, and visualization tools like Plotly and Tableau.