Data Analyst with Python, SQL, and Cloud Expertise

Mohan Gamidi

Data Analyst

Tampa, FL 656-***-**** ***********@*******.*** LinkedIn

Summary

Data Analyst with 4+ experience in Python, SQL, and cloud-based data platforms, delivering clean, reliable, and decision- ready datasets. Skilled in data analysis, EDA, and statistical methods to uncover trends, drivers, and actionable insights. Hands-on exposure to machine learning, predictive analytics, and AI-driven use cases supporting risk, fraud, and anomaly detection. Proven ability to build and optimize ETL pipelines, dashboards, and KPI frameworks with strong data quality and governance standards. Effective in Git-based version control, JIRA-driven delivery, and Confluence documentation, enabling structured, collaborative, and scalable analytics workflows. Skills

Data Analysis & Analytics: Python, SQL, Advanced Excel, Airflow, dbt, Data Cleaning & Transformation, Data Validation, Exploratory Data Analysis (EDA), Trend Analysis, Root Cause Analysis, Data-Driven Decision Support, A/B Testing Machine Learning & Advanced Analytics: Regression Analysis, Classification Models, Clustering Techniques, Feature Engineering, Model Training & Evaluation, Cross-Validation, Time-Series Forecasting, Predictive Analytics AI-Driven Analytics, BI & Visualization: Applied AI Use Cases, Anomaly Detection, Pattern Recognition, Risk & Fraud Analytics Support, Model Interpretability, Automation-Driven Insights, Tableau, Power BI, Looker, Dashboard Design & Optimization, KPI Frameworks, Executive & Operational Reporting, Data Storytelling, Customer Segmentation Statistical Analysis & Experimentation: Hypothesis Testing, Statistical Inference, Correlation Analysis, Cohort Analysis Data Engineering & ETL: ETL / ELT Pipelines, SQL-Based Transformations, Python-Based Data Processing, Data Warehousing Concepts, Schema Design, Data Lineage, Data Quality Checks, Git, JIRA, Confluence Cloud & Analytics Platforms: AWS S3, Redshift, Azure, BigQuery, Cloud-Based Analytics Workflows, Data Processing Governance, Quality & Compliance: Data Quality Frameworks, KPI Standardization, Reconciliation Processes, Metadata Management, Access Controls, Regulatory & Compliance Analytics Support Professional Experience

Data Analyst PNC Financials Jul 2025 – Present

Designed enterprise-level Tableau dashboards for credit risk and portfolio performance, transforming raw financial data into actionable insights, reducing manual reporting effort by 22% and improving leadership visibility into trends.

Automated recurring analytics workflows using advanced SQL and Python, streamlining data extraction, validation processes, and transformation that cut preparation time by 35% while increasing consistency across reports.

Partnered closely with Risk, Finance, and Compliance teams to define key risk indicators (KRIs), applying requirements analysis, KPI design, and trend analysis to identify shifts early, to support proactive business and regulatory decisions.

Built predictive machine learning models using Python and AWS-based data pipelines to forecast loan delinquency, improving model accuracy and directly influencing risk mitigation and portfolio optimization strategies.

Led comprehensive data-quality assessments across multiple upstream financial systems, performing root-cause analysis to identify inconsistencies and implement controls that improved downstream analytics trust by 40%.

Applied AI-driven anomaly detection techniques on high-volume transactional datasets to surface unusual activity patterns, strengthening fraud and risk monitoring capabilities while minimizing manual investigation effort. Data Analyst CueTech Systems Jan 2020 – Jul 2023

Analyzed large-scale customer, product, and usage datasets using SQL, exploratory data analysis (EDA), and cohort analysis to uncover behavioral trends, supporting data-backed product decisions that improved customer retention.

Developed and maintained scalable ETL pipelines using SQL and Python to consolidate data from multiple sources into a centralized warehouse, reducing reporting turnaround time by 50%.

Built interactive Power BI dashboards to track churn, revenue funnels, and engagement KPIs, enabling leadership teams to monitor performance in near real time and act faster on insights.

Applied machine learning modeling, customer segmentation, and behavioral analytics to identify high-value customer cohorts, enabling marketing teams to improve targeting strategies and drive higher conversion outcomes.

Executed statistical A/B testing frameworks using Python, R and Azure-based analytics workflows to evaluate new feature releases and pricing experiments, preventing low-impact rollouts and saving significant project costs.

Performed data cleaning and wrangling using Power Query (M) and DAX to standardize formats, resolve duplicates, and handle missing values across multiple sources, producing analysis-ready datasets for dashboards and reporting.

Designed analytics-ready data warehouse schemas (fact and dimension tables), documented data lineage and metric definitions in Confluence, and implemented data quality checks to validate data completeness and consistency. Education

Master’s in Business Analytics and Information Systems University of South Florida

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