Statistician

RemoteJobsOne

Paris

À distance

EUR 73 000 - 146 000

Temps partiel

Il y a 6 jours
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Résumé du poste

RemoteJobsOne is seeking a Statistician for a fully remote contractor role, open to candidates based in France. You will apply statistics to real-world data, support AI model training, and deliver quantitative insights.

Responsibilities include cleaning datasets, performing analyses, visualizing results, annotating data, and communicating findings to non-technical audiences, all in a remote, collaborative environment.

Qualifications

  • Advanced degree in a quantitative field.
  • Experience cleaning messy datasets.
  • Proficiency with Python or R for analysis.
  • Ability to communicate methods and results clearly.
  • Experience with large/unstructured data in remote settings.

Responsabilités

  • Clean and preprocess complex datasets using statistical software.
  • Apply descriptive and inferential analyses to real-world data.
  • Develop clear data visualizations to support model development.
  • Annotate and enrich datasets for AI model training.
  • Draft concise summaries of methods and results for non-technical audiences.
  • Collaborate asynchronously with stakeholders to refine deliverables.
  • Identify data quality issues and document remediation steps.

Connaissances

Statistical analysis
Data visualization
Written & verbal communication
Remote collaboration
Problem solving

Formation

MS/PhD in Statistics / Data Science

Outils

Python
R
SAS
Stata

Description du poste

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 France.

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.
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