QA Engineer

RIYA MARATHE

Pune, Maharashtra India 784******* *************@*****.***

Detail-oriented Data Science & Analytics Analyst with experience in data interrogation, validation, KPI monitoring, and trend analysis. Strong foundation in credit risk–related analytics, portfolio monitoring, and statistical analysis, with the ability to translate complex data into actionable, client-ready insights. Proficient in SQL, Python, Excel, Power BI, with exposure to forecasting, anomaly detection, and model validation aligned to TransUnion’s analytics solutions. EXPERIENCE

Numerator

Associate QA Engineer

• Construct, analyze, and interpret KPI and monitoring reports to ensure accuracy, reliability, and consistency of large-scale panel and market research datasets.

• Perform data interrogation, auditing, and validation to identify anomalies, inconsistencies, and potential data quality risks.

• Analyze data trends and patterns (sample size, continuity, balance metrics) and derive business-relevant insights to support decision-making.

• Conduct root cause analysis to resolve data quality issues and improve efficiency of analytical and reporting processes.

• Collaborate cross-functionally with Analytics, Operations, and Quality teams to deliver client-ready insights while ensuring GDPR compliance and data confidentiality. EDUCATION

Parul University, Vadodara

Bachelor of Computer Applications(BCA)

Bharati Vidyapeeth University (BVP), Pune

Master of Business Administration(MBA)

BUSINESS ANALYTICS & INFORMATION TECHNOLOGY MANAGEMENT PROJECT

Python, Time Series Analysis

Netflix Subscriptions Forecasting

• Conducted end-to-end data analysis including data cleaning, preprocessing, validation, and time-series forecasting (ARIMA) to identify trends and support strategic planning.

• Evaluated model performance using MAE and RMSE and translated analytical results into clear, decision-support insights for stakeholders

SKILLS

Credit Risk & Analytics:

Credit Risk Analytics, Portfolio Monitoring, Scorecard Support, KPI Monitoring, Monitoring Reports, Trend Analysis, Data Mining, Data Auditing & Validation, Data Quality Control, Anomaly Detection, Root Cause Analysis

Data Analysis & Statistical Techniques:

Exploratory Data Analysis (EDA), Descriptive Statistics, Regression Fundamentals, Forecasting Basics, Time Series Analysis, Model Validation Concepts, Quality Control Metrics Tools & Technologies:

SQL (MySQL, PostgreSQL), Python, Advanced Excel (Pivot Tables, Lookups, Charts), Power BI, KPI Dashboards

(SAS-ready analytical mindset; experience working with large structured datasets similar to SAS workflows) Data Management:

Data Interrogation, Data Transformation, Data Cleaning, ETL Concepts, Data Integrity, Data Warehousing Fundamentals

Business & Client Communication:

Client-Ready Reporting, Data Storytelling, Stakeholder Communication, Cross-Functional Collaboration, Presentation of Insights

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