Aryan A.

Key Skills

Software

No software listed

Top Subject Matter

Computer vision dataset annotation and AI output verification for training quality

Quantitative entity rating (stocks) for screening and risk reduction

Top Data Types

Image

Video

Text

Top Task Types

Text Generation

Object Detection

Question Answering

Text Summarization

Fine-tuning

Evaluation/Rating

Freelancer Overview

Research Intern, Equity & Quantitative Analysis. Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and Microsoft Excel. Education includes Bachelor of Commerce (Honours), Hansraj College, University of Delhi (2028) and Higher Secondary Certificate (CBSE), St. Xavier's School, Hazaribagh (2024). AI-training focus includes data types such as Image, Video, and Text and labeling workflows including Evaluation and Rating.

Labeling Experience

AI Data Analyst (Data Annotation & QA), Brainworks Remote, India (Mar 2026 – Jun 2026)

Image

Labeled 400–500 AI-generated art pieces using structured image and video tagging frameworks. Verified AI outputs by checking model-generated responses for factual and structural errors, then applying corrections to preserve data integrity. Performed geometric mapping and spatial labeling of visual datasets to support object-detection ground truth for production pipelines. • Annotated multimodal art content (images/videos) • Conducted systematic quality checks on AI outputs • Cleaned and standardized large-scale training datasets by removing mislabels/duplicates/low-quality entries • Ensured consistent labeling accuracy to improve CV model training

2026 - 2026

Research Intern - Equity & Quantitative Analysis, UNIVEST Gurugram (May 2025 – Jul 2025)

Text

Performed structured evaluation and rating of 25+ listed stocks using online sources and financial databases to support quantitative analysis. Built and applied rule-based screening logic in Excel to improve classification of stock breakouts for trading use cases. Although not classical dataset labeling, the work involved consistent criteria-based labeling/rating of entities for downstream decisioning. • Rated securities using structured rating criteria across multiple sectors • Implemented rule-based screening algorithm in Excel • Improved F&O analysis accuracy through consistent labeling logic • Produced analyst outputs to reduce investor risk exposure

2025 - 2025

Education

Work History