Nikita S.

Key Skills

Software

Mercor

OneForma

Internal/Proprietary Tooling

Top Subject Matter

LLM reasoning evaluation

factual consistency auditing

and structured AI output quality assessment (text).

Top Data Types

Text

Document

Audio

Top Task Types

Question Answering

Data Collection

Freelancer Overview

Data Quality & AI Evaluation Lead (Operations Lead & Data Evaluator) - FINDEM. Brings 7+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Google Sheets and Don't disclose. Education includes Master of Business Administration, Narsee Monjee Institute of Management Studies (NMIMS) and Bachelor of Commerce, K.C. Das Commerce College (2022). AI-training focus includes data types such as Text and Document and labeling workflows including Evaluation, Rating, and Question Answering.

Labeling Experience

Data Quality & AI Evaluation Lead (Operations Lead & Data Evaluator) - FINDEM

Text

Led AI data evaluation and quality operations by assessing system outputs and unstructured datasets against strict structured guidelines. Validated automated assessments and AI-driven pipelines, capturing reproducible error traces and flagging reasoning discrepancies prior to rollouts. Produced clear written justifications for quality dimensions to product and engineering teams to drive measurable improvements in error rates. • Evaluated outputs for factual consistency, logical soundness, and reasoning quality across 8-person team workflows. • Checked large unstructured datasets (8,000+ rows) and daily volumes of 2,000+ complex data points. • Tracked quality KPIs using Google Sheets to maintain adherence to evaluation standards. • Documented failure modes and reasoning discrepancies with reproducible evidence.

2024 - Present

Data Annotation & Quality Analyst - FINDEM

Don't discloseText

Executed rigorous visual, structural, and factual audits across foundational corporate datasets exceeding 2,000 records. Ensured consistent adherence to evaluation standards in a fast-paced, high-volume validation environment. Maintained high attention to detail while serving as a primary custodian of data accuracy. • Audited datasets for structural and factual correctness across 2,000+ records. • Performed repetitive quality checks to ensure consistency and reduce evaluation errors. • Validated foundational corporate data to support downstream AI-related workflows. • Documented quality findings to maintain standards for data accuracy.

2024 - 2024

Data Operations Project Specialist - FINDEM

Don't discloseTextQuestion Answering

Reviewed and evaluated complex unstructured backend content to transform ambiguous data arrays into logical, step-by-step business outputs. Applied analytical reasoning to troubleshoot contextual failures and support downstream curation workflows. Focused on improving interpretability and correctness of outputs for the broader data curation team. • Interpreted ambiguous unstructured data arrays into structured business-ready steps. • Evaluated contextual correctness to identify and troubleshoot reasoning failures. • Supported curation team by preparing logically ordered outputs from raw content. • Performed quality checks bridging evaluation and technical delivery.

2024 - 2024

Operations & Quality Analyst - FINDEM

Don't discloseText

Conducted error tracing and reasoning quality audits across foundational datasets exceeding 2,000 records. Captured reproducible error traces and documented failure modes within complex data pipelines to support quality improvement. Ensured ongoing consistency and accuracy through systematic review in a repetitive evaluation environment. • Performed quality audits and reasoning checks for datasets 2,000+ records. • Documented reproducible error traces to identify and analyze failure modes. • Maintained accuracy through systematic structuring and repeated validation. • Supported pipeline reliability by tracking and reporting quality issues.

2022 - 2023

Research Intern

Don't discloseDocumentData Collection

Assisted in the development of foundational data dictionaries and standard operating procedures (SOPs) to support early-stage data model validation. Prioritized methodology and accuracy when defining how data would be interpreted and validated. Helped establish reference materials used for consistent evaluation workflows. • Contributed to data dictionary creation for standardized labeling/validation definitions. • Developed SOPs to guide consistent evaluation methodology. • Supported early-stage accuracy and methodology checks for data models. • Helped define validation approaches for downstream AI/data work.

2021 - 2022

Education

Work History