Keshav M.

Key Skills

Software

Label Studio

Top Subject Matter

Customer support messages (Intent, Sentiment, PII)

Structured enterprise datasets for business insights

Forensic technology datasets and client reporting

Top Data Types

Text

Image

Document

Top Task Types

Classification

Data Collection

Text Summarization

Freelancer Overview

Data Labeling Analyst with hands-on experience in AI training data annotation, data quality validation, and analytical problem-solving. Worked on labeling 500+ customer support messages across Intent, Sentiment, and PII categories while maintaining 95%+ annotation accuracy. Developed standardized annotation guidelines for edge cases, improving consistency and workflow efficiency within the team. Strong background in data analysis using Python, SQL, Excel, and Tableau, with experience handling structured datasets and generating business insights. Graduated with a B.Tech from Indian Institute of Technology (IIT) Delhi and completed Data Analyst internships at Deloitte and TCS, where I worked on data preprocessing, exploratory analysis, KPI dashboards, and business reporting. Skilled in analytical reasoning, quality-focused execution, and collaborating on data-driven projects involving AI training data and business intelligence.

Labeling Experience

Data Analyst Intern (data classification & reporting)

OtherDocument

Analyzed forensic technology datasets in Excel by classifying 1,200+ records to surface patterns for business decision-making. Collaborated with an analytics team to translate raw data into structured business recommendations and client-ready outputs. Documented data workflows and findings in standardized reports used for client-facing presentations. • Classified 1,200+ records from forensic technology datasets • Translated analyzed data into structured recommendations • Documented workflows and findings for standardized reporting • Produced dashboarding outputs to support client reporting timelines

2025 - 2026

Data Analyst Intern (GenAI exploratory analysis)

OtherTextData Collection

Used GenAI tools to conduct exploratory analysis on 3 structured enterprise datasets and surface 5+ trends per dataset. Cleaned and preprocessed business data with Python (Pandas) to improve dataset quality by 25% before analysis. Produced insight reports with actionable recommendations supporting simulated strategic planning decisions across business functions. • Performed exploratory analysis using GenAI-assisted workflows • Preprocessed and cleaned structured datasets using Pandas • Synthesized findings into multiple insight reports with recommendations • Analyzed cross-functional patterns across sales, operations, and HR datasets

2025 - 2025

Data Labeling Analyst

Don't discloseTextClassification

Classified 500+ real-world customer support messages into Intent, Sentiment, and PII label categories using predefined annotation schemes. Implemented standardized decision logic for ambiguous edge cases to improve annotation consistency across the team. Validated and reviewed 500+ annotations against quality benchmarks to maintain a 95%+ accuracy rate. • Labeled messages by intent, sentiment, and PII presence/categories • Built reusable guidelines by documenting rationales for 3 ambiguous case categories • Performed quality checks and benchmark-based validation of annotations • Worked on maintaining labeling consistency for edge cases

2025 - 2025

Education

Work History