Use your expertise to train leading AI models
Statistician
Am I a fit — voir ma compatibilitéJT AI Labs recherche un Statistician freelance pour contribuer à un projet client consacré à l’amélioration de solutions fondées sur les données et à l’entraînement de systèmes d’IA. La mission comprend le nettoyage de jeux de données complexes, les analyses statistiques, la visualisation des résultats et l’enrichissement de données d’entraînement, avec R, Python, SAS ou Stata. Le poste est exercé à distance et requiert un diplôme avancé en statistiques, data science, mathématiques, biostatistiques ou domaine quantitatif connexe.
Repères sur JT AI Labs
- Offres ouvertes
- 41
Détails de l’offre
La description complète publiée par JT AI Labs.
Description de l’offre
Role Title: Statistician
Role Type: Contractor
Location: Remote
micro1 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
- Clean, preprocess, and structure complex and messy datasets using advanced statistical software (such as R, Python, SAS, or Stata).
- Apply and document basic descriptive and inferential statistical analyses to uncover trends and patterns in real-world data.
- Develop clear and compelling data visualizations to illustrate key findings and support model development.
- Contribute expertise in dataset annotation, labeling, or enrichment to enhance the quality of AI model training datasets.
- Draft concise, well-organized written summaries of methods, analyses, and results for a non-technical audience.
- Collaborate asynchronously with project stakeholders to clarify requirements, resolve ambiguities, and improve deliverables through effective written and verbal communication.
- Continuously identify data quality issues, provide actionable recommendations, and document solutions for handling dirty or incomplete data.
Preferred
Qualifications
- Advanced degree (MS or PhD) in Statistics, Data Science, Mathematics, Biostatistics, or a related quantitative field.
- Expertise in cleaning and preparing complex, messy (“dirty”) datasets with R, Python, SAS, or Stata.
- Proficiency in basic descriptive and inferential statistical techniques, including hypothesis testing and regression analysis.
- Strong programming skills in Python or R for statistical analysis, data manipulation, and visualization.
- Demonstrated ability to communicate complex findings to non-technical and technical audiences with clarity and precision.
- Experience working with large, unstructured, or noisy datasets across a variety of domains.
- Excellent written and verbal communication skills, with a focus on detailed documentation and collaboration in remote environments.
Prérequis
- Techniques statistiques descriptives et inférentielles
- Tests d’hypothèse
- Analyse de régression
- Communication écrite et orale
- Documentation détaillée
- Collaboration à distance