At a Glance
- Tasks: Clean and analyse complex datasets to support AI training and data-driven solutions.
- Company: Join micro1, a forward-thinking company focused on innovative data solutions.
- Benefits: Earn $60β$120/hr with flexible remote work opportunities.
- Other info: Collaborate remotely and enjoy excellent career growth potential.
- Why this job: Make a real impact by applying your statistical skills to exciting AI projects.
- Qualifications: Experience in statistics and programming with Python or R is essential.
The predicted salary is between 120 - 120 Β£ per hour.
- Statistician
- Position: Statistician
- Type: Hourly Contract
Compensation: $60β$120/hour
About the Opportunity micro1 is engaging experienced Statisticians to contribute to a customer project focused on advancing data-driven solutions and training next-generation AI systems.
In this role, you will apply practical statistical expertise to data cleaning and preparation, descriptive and inferential analysis, programming, visualization, dataset enrichment, and communicating analytical findings.
You will work with real-world datasets that may be incomplete, inconsistent, noisy, or otherwise challenging, providing high-quality domain input that helps AI systems learn to reason more effectively with data.
No prior AI experience is required. Your statistical expertise, analytical judgment, programming ability, and communication skills are what matter most.
Responsibilities
- Clean, preprocess, validate, and structure complex or messy datasets using statistical tools such as R, Python, SAS, or Stata.
- Identify and address missing values, inconsistencies, outliers, formatting issues, and other data-quality problems.
- Apply appropriate descriptive and inferential statistical techniques to identify trends, patterns, relationships, and meaningful findings.
- Document statistical methods, assumptions, analytical decisions, and results clearly.
- Develop effective data visualizations that communicate analytical findings and support data-driven decision-making.
- Contribute expertise to dataset annotation, labeling, enrichment, and quality review activities supporting AI model training.
- Prepare concise and well-structured summaries of analytical methods, findings, and conclusions for non-technical audiences.
- Collaborate asynchronously with project stakeholders to clarify requirements, resolve analytical ambiguities, and improve deliverables.
- Communicate statistical findings effectively to both technical and non-technical stakeholders.
- Identify recurring data-quality challenges and recommend practical approaches for handling incomplete, noisy, or inconsistent datasets.
- Maintain accurate documentation of data preparation, analysis, and solutions.
- Required Qualifications
- Professional experience applying statistics to real-world datasets and analytical problems.
- Strong ability to clean and prepare complex or messy data.
- Working knowledge of descriptive and inferential statistics.
- Experience using Python or R for statistical analysis and data manipulation.
- Ability to create clear and informative data visualizations.
- Understanding of statistical concepts including hypothesis testing and regression analysis.
- Ability to communicate analytical findings clearly to non-technical audiences.
- Strong analytical reasoning and attention to detail.
- Excellent written and verbal communication skills.
- Ability to work independently and collaborate effectively in a remote environment.
- Preferred Qualifications
- Advanced degree such as an MS or Ph D in Statistics, Data Science, Mathematics, Biostatistics, or a related quantitative field.
- Strong experience cleaning and preparing complex, messy, noisy, or incomplete datasets.
- Proficiency with R, Python, SAS, or Stata.
- Strong programming skills for statistical analysis, data manipulation, and visualization.
- Experience applying descriptive and inferential methods, including hypothesis testing and regression analysis.
- Experience working with large, unstructured, or noisy datasets across multiple domains.
- Experience with dataset annotation, labeling, enrichment, or AI data-quality workflows.
- Demonstrated ability to translate complex statistical findings into clear business or operational insights.
- Strong documentation and remote collaboration skills.
- Key Areas of Expertise
- Statistical analysis
- Data cleaning and preparation
- Dirty and noisy data
- Descriptive statistics
- Inferential statistics
- Hypothesis testing
- Regression analysis
- Python
- R
- SAS
- Stata
- Data manipulation
- Data visualization
- Dataset annotation
- Data labeling and enrichment
- Data quality
- Statistical documentation
- Analytical communication
- AI training data
Compensation & Engagement
- Remote contract opportunity.
- Work focuses on applying statistical expertise to real-world data and AI training scenarios.
- Tasks may involve data preparation, statistical analysis, visualization, dataset enrichment, and analytical documentation.
- No prior AI experience is required.
- Application Process
- Submit an updated resume highlighting your statistical, quantitative, programming, and data-analysis experience.
- Complete the initial application and screening process.
- Participate in a short AI interview focused on your professional background and statistical expertise.
- Complete a statistics or data-analysis assessment if required.
- Following review and approval, begin contributing to the project.
- Start Timeline & Availability
Selected professionals should be able to work independently, communicate analytical findings clearly, and deliver accurate statistical work within project requirements.
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