Priyanka S.

Key Skills

Software

Don't disclose

Top Subject Matter

AI output/response validation and data accuracy QA for web/mobile/API systems

AI evaluation-aligned QA for mobile application output quality

Top Data Types

Text

Top Task Types

Text Generation

Question Answering

Text Summarization

Fine-tuning

Evaluation/Rating

Computer Programming/Coding

Prompt + Response Writing (SFT)

Data Collection

Classification

Freelancer Overview

Test Engineer (AI evaluation/data validation aligned QA) at TCS (Vodafone UK; Sainsbury’s UK). Brings 10+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose. Education includes Master of Science in Software Engineering with Cloud Computing, City, University of London (2024) and Bachelor of Technology, Gitam University (2017). AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

Labeling Experience

Communications Captain (quality validation and output/data accuracy assessment) at Welcome Break

Don't discloseText

Applied QA principles to validate application outputs with an emphasis on response and data accuracy verification. Conducted testing and reporting activities to identify issues that could affect data correctness and user-facing behavior. Enhanced validation reporting efficiency by tracking results and communicating findings for faster resolution. • Validated mobile application outputs for correctness • Improved reporting efficiency by 30% through better QA documentation • Coordinated issue resolution with technical teams • Ensured data accuracy during quality assessment workflows

2024 - 2026

Test Engineer (AI evaluation/data validation aligned QA) at TCS (Vodafone UK; Sainsbury’s UK)

Don't discloseText

Performed AI-oriented evaluation of system outputs by applying QA validation practices to ensure responses and outputs were accurate and consistent with expected results. Supported defect identification and data quality checks to improve reliability of application behavior and data returned by APIs. Used structured test case design to assess whether observed outputs matched expected criteria. • Evaluated API/system outputs for correctness and consistency • Identified and documented defects impacting data accuracy • Validated financial and domain-specific data using SQL • Coordinated issue resolution with technical stakeholders

2017 - 2022

Education

Work History