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I’m Mira Radhakrishnan, an AI Data Analyst based in Dallas with 4+ years of experience supporting Generative AI systems across LLM data annotation, dataset training/evaluation, and output testing. I help teams build high-quality labeling and evaluation processes by creating annotation guidelines, quality rubrics, and QC workflows that catch issues like hallucinations, edge cases, and schema or formatting errors before they impact model performance.…I’m Mira Radhakrishnan, an AI Data Analyst based in Dallas with 4+ years of experience supporting Generative AI systems across LLM data annotation, dataset training/evaluation, and output testing. I help teams build high-quality labeling and evaluation processes by creating annotation guidelines, quality rubrics, and QC workflows that catch issues like hallucinations, edge cases, and schema or formatting errors before they impact model performance.

Mira Radhakrishnan

Data Analyst, AI Evaluator, Data Annotator

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I’m Mira Radhakrishnan, an AI Data Analyst based in Dallas with 4+ years of experience supporting Generative AI systems across LLM data annotation, dataset training/evaluation, and output testing. I help teams build high-quality labeling and evaluation processes by creating annotation guidelines, quality rubrics, and QC workflows that catch issues like hallucinations, edge cases, and schema or formatting errors before they impact model performance.…I’m Mira Radhakrishnan, an AI Data Analyst based in Dallas with 4+ years of experience supporting Generative AI systems across LLM data annotation, dataset training/evaluation, and output testing. I help teams build high-quality labeling and evaluation processes by creating annotation guidelines, quality rubrics, and QC workflows that catch issues like hallucinations, edge cases, and schema or formatting errors before they impact model performance.

Available to hire

I’m Mira Radhakrishnan, an AI Data Analyst based in Dallas with 4+ years of experience supporting Generative AI systems across LLM data annotation, dataset training/evaluation, and output testing. I help teams build high-quality labeling and evaluation processes by creating annotation guidelines, quality rubrics, and QC workflows that catch issues like hallucinations, edge cases, and schema or formatting errors before they impact model performance.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Work Experience

Data Analyst – Gen AI at Keywords Studios (Amazon AGI)

June 1, 2025 - Present

Curated, annotated, and validated high-quality LLM training and evaluation datasets for e-commerce workflows such as account creation, subscriptions, checkout, and payments. Defined and evaluated dataset quality metrics supporting RL pipelines, including accuracy, consistency, reviewer agreement, and alignment with model learning objectives. Performed QC and side-by-side evaluations of LLM outputs to identify annotation gaps, quality deviations, ambiguous cases, hallucinations, and edge cases. Validated JSON schemas and structured data (CSV/text) for schema compliance and accurate workflow representation. Developed annotation guidelines, evaluation rubrics, and feedback processes to standardize labeling decisions and improve reviewer agreement. Built 20+ automated Hex dashboards to monitor annotation accuracy, reviewer agreement, throughput, dataset health, and evaluation outcomes, reducing manual reporting efforts by 40%.

Data Analyst - Gen AI at Data Reveal AI LLC

January 1, 2025 - April 30, 2025

Collected, annotated, and validated structured and unstructured datasets from APIs and external sources to support Generative AI and LLM development. Conducted LLM and chatbot testing and evaluations using response quality assessment, prompt testing, annotation reviews, error analysis, and edge-case testing, translating findings into recommendations to improve model accuracy. Built Power BI dashboards and KPI scorecards to monitor dataset quality, annotation accuracy, evaluation metrics, AI workflow performance, and operational metrics.

Data Analyst at Sports Excitement

August 1, 2024 - December 31, 2024

Analyzed customer behavior, product, and engagement datasets using SQL and Python to identify behavioral patterns, data issues, and opportunities for AI-driven automation. Designed and optimized prompt workflows for multi-agent AI applications by defining use cases, creating task-specific prompts, and developing evaluation scenarios to assess agent reasoning and response quality. Built Tableau dashboards to monitor customer insights, business KPIs, product metrics, and AI workflow performance, enabling data-driven decisions and operational improvements.

Data Analyst at Tata Consultancy Services

January 1, 2022 - September 30, 2022

Built and optimized 50+ data pipelines using Python and SQL to ingest, transform, and prepare multi-source datasets from APIs and operational systems for analytics and ML-driven applications. Designed scalable cloud-based data workflows using AWS S3, Glue, Lambda, Snowflake, and dbt to deliver analytics-ready datasets for ML applications. Developed Tableau and Power BI dashboards to analyze customer behavior, sales performance, and operational KPIs. Partnered with business and technical stakeholders to translate requirements into data models, dashboards, and performance reporting frameworks supporting strategic decision-making.