Statistician

RemoteJobsOne; Amsterdam; Remote; EUR 73,000 - 146,000; Part time

Job summary

RemoteJobsOne is seeking a Statistician contractor to contribute expert knowledge to a customer project advancing data-driven AI systems. You will apply your expertise to help train next-generation models and shape how they learn, reason, and perform.

The role emphasizes strong data cleaning, descriptive and inferential analyses, and clear communication of methods to non-technical stakeholders. Remote work is available for candidates based in the Netherlands.

Qualifications

• Advanced degree or higher in a quantitative field.
• Ability to clean and prepare messy datasets.
• Familiarity with descriptive and inferential statistics.
• Proficient in Python or R for analysis and visualization.
• Excellent written/verbal communication for technical and non-technical audiences.

Responsibilities

• Clean, preprocess, and structure complex datasets using statistical software.
• Apply descriptive and inferential analyses to real-world data.
• Develop clear data visualizations to illustrate findings.
• Annotate and enrich datasets to improve AI model training quality.
• Summarize methods and results for non-technical audiences.
• Collaborate asynchronously with stakeholders to clarify requirements.
• Identify data quality issues and document remediation steps.

Skills

Advanced degree

Dirty data handling

Statistical techniques

Python

R

Communication

Big data

Education

MS or PhD in Statistics or related

Tools

Python

R

SAS

Stata

Job description

IMPORTANT: after you apply, please check your email. We send you a link to complete your application — it is not considered until that last step is done. If you do not see it, check your spam folder.

This is a fully remote position, open to candidates based in Netherlands.

Pay: $60–$120/hr

Role Title: Statistician

Role Type: Contractor

Location: Remote

the company is selecting Statistician to contribute expert knowledge to a customer project focused on advancing data-driven solutions. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

Scope of Work

1. Clean, preprocess, and structure complex and messy datasets using advanced statistical software (such as R, Python, SAS, or Stata).
2. Apply and document basic descriptive and inferential statistical analyses to uncover trends and patterns in real-world data.
3. Develop clear and compelling data visualizations to illustrate key findings and support model development.
4. Contribute expertise in dataset annotation, labeling, or enrichment to enhance the quality of AI model training datasets.
5. Draft concise, well-organized written summaries of methods, analyses, and results for a non-technical audience.
6. Collaborate asynchronously with project stakeholders to clarify requirements, resolve ambiguities, and improve deliverables through effective written and verbal communication.
7. Continuously identify data quality issues, provide actionable recommendations, and document solutions for handling dirty or incomplete data.

Preferred Qualifications

1. Advanced degree (MS or PhD) in Statistics, Data Science, Mathematics, Biostatistics, or a related quantitative field.
2. Expertise in cleaning and preparing complex, messy (“dirty”) datasets with R, Python, SAS, or Stata.
3. Proficiency in basic descriptive and inferential statistical techniques, including hypothesis testing and regression analysis.
4. Strong programming skills in Python or R for statistical analysis, data manipulation, and visualization.
5. Demonstrated ability to communicate complex findings to non-technical and technical audiences with clarity and precision.
6. Experience working with large, unstructured, or noisy datasets across a variety of domains.
7. Excellent written and verbal communication skills, with a focus on detailed documentation and collaboration in remote environments.