Data & Analytics
Hire Data Scientists
Data scientists use statistics and modelling to predict outcomes, segment customers, run experiments and find patterns in your data.
The role
What data scientists do
A data scientist explores data, builds statistical or machine learning models, designs and analyses A/B tests, and communicates findings with appropriate uncertainty. Much of the value comes from framing problems well and avoiding misleading conclusions.
Typical deliverables
- Forecasts and predictive models
- Customer segmentation
- A/B test design and analysis
- Statistical reports
- Reproducible notebooks and code
Tools you will see
- Python or R
- pandas
- scikit-learn
- statsmodels
- Jupyter
- SQL
Choosing
How to choose data scientists
What to look for
- Clear explanation of methods and uncertainty.
- Projects with business impact, not only competitions.
- Checks against overfitting and data leakage.
- Code others can rerun.
Questions to ask
- 1How would you frame this as a data problem?
- 2How would you measure success?
- 3How do you communicate uncertainty in results?
- 4What would make this model unreliable?
Planning
Before you post the job
Data readiness
If data is scattered or messy, data engineering may be needed before data science.
What drives cost
Data preparation, modelling complexity, experimentation and deployment.
Hiring on Open Lance
- Posting a job and reviewing proposals are free.
- Each milestone is funded into escrow before work starts and paid when you approve it.
- Hire fixed-price, hourly, as a monthly Dedicated Hire, or buy a packaged Drop-In.
- Client fees are shown before you pay and added on top of the work.
FAQ
Questions about hiring data scientists
Do we need a data scientist or an analyst?
An analyst explains past performance. A data scientist builds forecasts, models and experiments.
Can a data scientist deploy models?
Some can. Production deployment often benefits from ML engineering or MLOps skills.
How do we run a valid A/B test?
Define the metric and sample size before starting, and avoid stopping early when results look good.
Related
Related skills
Post a job for data scientists
Describe the work and compare proposals. You only fund the first milestone once you have chosen someone.