The Ai Training Company
Data Analyst | €52/hr | Remote

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Data Analysts, Data Quality & Business Data Review Specialists. Remote AI Project
We are seeking experienced Data Analysts, Business Data Analysts, Data Quality Specialists, Data Reviewers, and Data Governance Professionals to support a high-impact AI training project focused on large-scale business data.
You will review, analyze, validate, and quality-check datasets and documents while ensuring strict adherence to privacy, security, and personally identifiable information (PII) requirements.
What You’ll Do
- Review and analyze large business datasets
- Validate data for accuracy, completeness, consistency, and relevance
- Identify missing values, duplicate records, anomalies, and incorrect data
- Review documents containing structured and unstructured business information
- Apply strict data privacy and PII-handling requirements
- Identify and flag sensitive or personally identifiable information
- Perform data validation and quality assurance checks
- Investigate data inconsistencies and determine likely root causes
- Document data-quality issues clearly
- Provide recommendations to improve data accuracy and integrity
- Apply project-specific quality standards and review guidelines
- Contribute to the improvement of QA processes, checklists, and evaluation criteria
- Communicate findings clearly to project stakeholders
- Maintain compliance with privacy, security, and data-handling requirements
- Work independently in a remote, distributed project environment
Who Can Apply
Relevant backgrounds include:
- Data Analysts, Senior Data Analysts, Business Data Analysts, Business Analysts, Data Quality Analysts, Data Quality Specialists, Data Review Analysts, Data Validation Analysts, Data Integrity Analysts, Data Operations Analysts, and Data Management Analysts.
- Quality Analysts, Quality Assurance Analysts, QA Analysts, Data QA Specialists, Data Auditors, Data Reviewers, Quality Reviewers, Quality Control Analysts, QC Analysts, and Data Accuracy Specialists.
- Data governance and privacy backgrounds may include: Data Governance Analysts, Data Governance Specialists, Data Privacy Analysts, Privacy Operations Specialists, Information Governance Analysts, Data Compliance Analysts, Data Stewardship Professionals, Data Stewards, and Information Management Specialists.
- Business and operations backgrounds may include: Operations Analysts, Business Operations Analysts, Process Analysts, Reporting Analysts, Research Analysts, Risk Analysts, Compliance Analysts, Audit Analysts, and Business Intelligence Analysts with strong data-review experience.
- Document-review backgrounds may include: Document Review Specialists, Document Analysts, Records Analysts, Information Management Specialists, Documentation Specialists, Compliance Reviewers, Audit Reviewers, and Quality Assurance Reviewers.
- AI and evaluation backgrounds may include: AI Data Analysts, AI Evaluators, Data Annotators, Data Labelers, Human Feedback Specialists, Model Evaluators, AI Quality Analysts, Annotation Quality Specialists, and Rubric Evaluators.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Relevant Data Analysis Experience
Strong candidates may have experience with:
- Data cleaning
- Data validation
- Data reconciliation
- Data profiling
- Data auditing
- Data quality assessment
- Data integrity checks
- Duplicate detection
- Missing data analysis
- Outlier detection
- Anomaly detection
- Data standardization
- Data normalization
- Data matching
- Record linkage
- Data enrichment
- Data transformation
- Data verification
- Data classification
- Data annotation
- Data review
- Dataset documentation
- Quality-control workflows


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Requirements
- Professional experience in data analysis, data quality, document review, business analytics, data governance, QA, audit, or a closely related field
- Demonstrated ability to work with large business datasets
- Experience identifying data errors and inconsistencies
- Strong attention to detail
- Ability to review sensitive information carefully
- Understanding of data privacy and PII-handling principles
- Strong analytical and problem-solving skills
- Ability to clearly document findings and recommendations
- Strong written and verbal communication
- Ability to follow detailed quality and privacy guidelines
- Comfortable working independently in a remote environment
- Consistent and reliable delivery of high-quality work
Preferred Background
- Experience working with personally identifiable information
- Experience with sensitive or confidential business data
- Experience conducting data audits
- Experience with document review
- Experience in data quality assurance
- Experience with privacy compliance or data governance
- Experience building or applying data-quality standards
- Experience reviewing work produced by other analysts
- Experience using Excel, SQL, Python, Tableau, or Power BI
- Experience with CRM, finance, operations, or customer datasets
- Experience creating SOPs, checklists, or QA processes
This opportunity is ideal for professionals who can look at a large dataset or collection of documents and quickly identify what is missing, inconsistent, inaccurate, sensitive, or potentially risky, then document the issue clearly and help improve overall data quality. We are a referral partner of the client.
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