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Sinthujah Gunasekaram

AI Data Quality Consultant

Canada flagToronto, Canada
$30.00/hrExpertLabel StudioScale AIOther

Key Skills

Software

Label StudioLabel Studio
Scale AIScale AI
Other
Internal/Proprietary Tooling

Top Subject Matter

AI Data Quality and Evaluation
Natural Language Processing Data Quality
Legal Services & Contract Review

Top Data Types

TextText
AudioAudio
DocumentDocument

Top Task Types

Classification
Question Answering
Red Teaming
Transcription
Evaluation Rating
Data Collection

Freelancer Overview

Over the past three years, I have built hands-on experience in AI data quality and annotation across two major AI companies — Cohere and Replicant. At Cohere, I reviewed and annotated 10,000+ records, ensuring accurate labeling, ranking, and auditing of AI/ML datasets while consistently exceeding quality benchmarks across multiple concurrent pipelines. At Replicant, I leveled up into more technical territory, developing and executing structured evaluation test suites to measure LLM performance, refining system prompts, and optimizing multi-turn conversation flows to improve model clarity and customer-facing responses. What sets me apart is the combination of technical fluency and domain knowledge I bring to this work. I am comfortable working directly in GitHub, GitLab, and VS Code for version control and prompt engineering updates, and I use Excel and Google Sheets extensively for error categorization, dataset tracking, and quality trend analysis. My background in Public Health and Safety also gives me a strong foundation in data ethics, confidentiality protocols, and the importance of accuracy in high-stakes contexts, which translates well to responsible AI development work.

ExpertTamilEnglish

Labeling Experience

AI Data Quality Consultant

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As an AI Data Quality Consultant at Replicant, I performed first-level triage and investigations on data quality issues, validating AI system outputs and documenting resolutions. I conducted quality assurance reviews of datasets and evaluation outputs, identifying inconsistencies and degradation trends before downstream impact. I analyzed recurring data quality issues, categorized root causes, and reported findings to stakeholders to improve reliability. • Performed recurring reviews of structured and unstructured text datasets. • Monitored evaluation pipelines and coordinated technical resolutions with engineering teams. • Developed and maintained documentation for QA processes and standards. • Handled 25–40 data quality escalations per cycle.

As an AI Data Quality Consultant at Replicant, I performed first-level triage and investigations on data quality issues, validating AI system outputs and documenting resolutions. I conducted quality assurance reviews of datasets and evaluation outputs, identifying inconsistencies and degradation trends before downstream impact. I analyzed recurring data quality issues, categorized root causes, and reported findings to stakeholders to improve reliability. • Performed recurring reviews of structured and unstructured text datasets. • Monitored evaluation pipelines and coordinated technical resolutions with engineering teams. • Developed and maintained documentation for QA processes and standards. • Handled 25–40 data quality escalations per cycle.

2025 - Present

Senior Data Quality Specialist

Text
As a Senior Data Quality Specialist at Cohere, I audited over 10,000 data samples for accuracy, consistency, and schema compliance in large-scale data pipelines. I led the investigation and escalation of data discrepancies, validating outputs and documenting findings for engineering and product teams. I developed and scaled annotation guidelines, QA checklists, and review standards, and tracked recurring issues to guide improvements. • Supported 3–5 concurrent data workflows, monitoring progress and identifying failure patterns. • Assisted in refining annotation, QA processes, and review standards for text data. • Acted as first point of escalation for data quality and labeling issues. • Used SQL and spreadsheets for trend analysis and validation.

As a Senior Data Quality Specialist at Cohere, I audited over 10,000 data samples for accuracy, consistency, and schema compliance in large-scale data pipelines. I led the investigation and escalation of data discrepancies, validating outputs and documenting findings for engineering and product teams. I developed and scaled annotation guidelines, QA checklists, and review standards, and tracked recurring issues to guide improvements. • Supported 3–5 concurrent data workflows, monitoring progress and identifying failure patterns. • Assisted in refining annotation, QA processes, and review standards for text data. • Acted as first point of escalation for data quality and labeling issues. • Used SQL and spreadsheets for trend analysis and validation.

2023 - 2024

Education

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Toronto Metropolitan University

Bachelor of Science, Public Health and Safety

Bachelor of Science
2021

Work History

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The Neighbourhood Group Community Services

Case Worker Assistant

Toronto
2022 - 2022