Noida, Uttar Pradesh, India
I am currently upskilling in Data Science, focusing on Python, SQL, Machine Learning, and Data Visualization. Passionate about using data-driven insights to solve real-world problems. Excited to connect with like-minded professionals and learn from industry experts.
Stakeholder Reporting & KPI Management: Designed and delivered structured performance reports and dashboards tracking key quality KPIs, error rates, and data pipeline metrics for senior stakeholders, enabling data-driven decisions across Operations and Technology teams. Business Requirement Analysis: Identified bottlenecks and edge cases in ML annotation workflows through root-cause analysis; collaborated with cross-functional teams to define process improvements that reduced error rates and optimised pipeline throughput. Data Quality & Validation: Annotated, validated, and processed large-scale multilingual datasets for Amazon Just Walk Out technology, consistently achieving high accuracy benchmarks through rigorous quality checks. EDA & Insight Generation: Performed exploratory data analysis on dataset inconsistencies across language segments, identifying systematic error patterns and recommending targeted validation checkpoints that improved data consistency. Process Documentation & SOPs: Produced comprehensive SOPs and process documentation standardising annotation workflows, onboarding procedures, and quality review frameworks for cross-team adoption. AI-Assisted Workflow Automation: Leveraged AI tools (ChatGPT, Gemini, Claude) to automate repetitive validation tasks, accelerate gap detection in multilingual datasets, and synthesise quality review findings into actionable summaries — reducing manual effort by ~30%.
Conduct thorough reviews of user-generated content, including text, images, and videos, to ensure compliance with community standards and guidelines. Collaborate with cross-functional teams to develop and refine moderation processes, improving efficiency and effectiveness.