Mariya Fatima

Data Analyst | Business Analytics & BI

Hyderabad, HyderabadMember since November 12, 2025

PythonSQLPostgreSQLDAXPower BITableauExcelMatplotlibpandasXGBoostRegressionK-Means clusteringMonte Carlo simulationTime-series forecastingJupyter NotebookJavaJavaScriptCSS

About

Data Analyst with an MBA in Business Analytics and a B.Tech in Computer Science, combining strong technical foundations with applied experience in AI/LLM data quality work. Skilled in Python, SQL, Power BI, Tableau, Excel, and R, with hands-on experience building predictive models (regression, XGBoost, K-Means), interactive dashboards, and DAX-driven data models across eight analytics projects. Proven ability to transform raw, multi-source data into forecasts and decision-ready insights; seeking a Data Analyst role to apply data modeling, transformation, and visualization skills to drive business outcomes.

Experience

AI/LLM Analyst - Innodata Inc. - Remote, Full-time

(2026-02 - 2026-07)

Reviewed and refined AI-generated responses and training data for accuracy, coherence, and alignment, directly supporting large language model fine-tuning and data quality initiatives.
Built and validated high-quality training datasets by applying structured data quality checks, correcting grammar, syntax, and factual inconsistencies across human- and AI-generated content.
Consistently met all production KPIs — daily job count, average handle time, and production hours — while maintaining accuracy and compliance with quality and ethical guidelines.
Documented detailed feedback and rationale for iterative model improvement, translating qualitative review into structured, actionable data points.

Business Analytics Intern - Wayspire – Business Analytics - Remote

(2025-07 - 2025-09)

Completed hands-on training across 4 live projects covering Python, machine learning, data visualization (Tableau), data mining, and business analytics.
Project 1 – Data Analysis & Visualization: Analyzed datasets and built visualizations using Python, pandas, and Matplotlib to surface business insights.
Project 2 – EDA & Regression: Performed exploratory data analysis and applied linear/logistic regression and classification models to evaluate relationships in the data.
Project 3 – Time-Series Forecasting: Built forecasting models and applied clustering/classification techniques for advanced business intelligence analysis.
Project 4 – Predictive Modeling: Ran EDA on the Adult Income Dataset, resolved data quality issues, and applied classification models to predict income levels.