Data Analyst Power Bi

Navya Teja Pathuri

Data Analyst

+1-980-***-**** # *******************@*****.*** ï LinkedIn

Professional Summary

• Data Analyst with 3+ years of experience in transforming complex datasets into actionable business strategies, specializing in marketing analytics, customer insights, and data-driven decision-making.

• Proficient in SQL, Python, Tableau, Power BI, and Excel for building dashboards, performance reporting, and ad-hoc analysis.

• Experienced in automating ETL pipelines using AWS Glue, S3, and Snowflake to process large-scale datasets efficiently.

• Expertise in A/B testing, predictive modeling and statistical analysis to improve CTR, optimize campaigns, and drive marketing-attributed revenue.

• Hands-on with marketing attribution, funnel analysis, and performance tracking using Google Analytics and CDPs.

• Strong background in customer journey mapping, cohort analysis, and marketing funnel optimization, improving audience targeting and increasing re-engagement.

• Effective collaborator with marketing, sales, and engineering teams to drive measurable business impact. Work Experience

CGI Inc. June 2024 – Present

Data Analyst United States

• Led a customer-facing energy forecasting initiative for a utility client, using smart meter data to reduce high-bill complaints by 25% and improve customer satisfaction scores.

• Built scalable ETL pipelines in AWS Glue and S3 to clean and structure daily consumption data from 30,000+ households, improving data readiness and reducing processing time by 90%.

• Developed individualized forecasting models using Facebook Prophet, achieving 18% MAPE - aligned with the utility’s 15–20% accuracy target.

• Integrated forecasts into the utility’s mobile app, enabling 80% of users to receive alerts when bills were expected to exceed their average by 15% or more.

• Monitored forecast accuracy and model drift using Tableau dashboards, enabling data teams to catch anomalies and maintain reliability across user segments.

• Designed a Power BI dashboard with drill-down capability for product and region-level KPIs, used by senior leadership in quarterly business reviews.

• Integrated forecast results with Tableau dashboards and internal reporting tools to monitor forecast accuracy, model drift, and campaign outcomes across user segments. Hexaware Technologies April 2021 – July 2023

Data Analyst India

• Analyzed marketing campaigns using KPIs like click-through rate, bounce rate, and revenue per session, improving ROI by 22%.

• Recommended and implemented a Customer Data Platform to track real-time user behavior, enabling targeted campaigns and fixing blind spots in existing outreach strategy.

• Created customer segments based on engagement levels using CDP data, improving campaign personalization and leading to a 17% increase in user engagement.

• Built targeted ads for professors who hadn’t seen the free book offer, increasing conversion from 8% to 12% and generating $380,000 in additional revenue from course-related student purchases.

• Set up automated pipelines to send user behavior data from the CDP to Salesforce, helping the sales team reach out with discounts and EMI offers, which led to a 14% increase in conversions.

• Developed Tableau dashboards to visualize campaign engagement, segment performance, and funnel metrics, helping marketing teams make faster decisions and reduce spending inefficiencies by 15%.

• Created weekly campaign performance reports using Google Analytics and Excel, reducing manual reporting effort by 60% and improving visibility for non-technical stakeholders.

• Forecasted product demand using Prophet models, improving inventory decisions and reducing excess stock by 18% for key textbook categories.

Skills

Programming & Tools: Python, R, SQL, JavaScript, C, Ruby, HTML, CSS. Databases: Snowflake, MySQL, PostgreSQL, Oracle, MongoDB, Redshift, SQL Server. Data Visualization: Tableau, Power BI, Looker, Matplotlib, Seaborn, Plotly. ETL & Data Engineering: Apache Airflow, DBT, Azure Data Factory, SSIS, Alteryx, PySpark, Kafka, CDC Pipelines.

Big Data & Cloud Technologies: AWS (S3, Redshift, Glue, Lambda), Azure (Databricks, Synapse Analytics, Data Factory, CosmosDB), Google Cloud (BigQuery, Cloud Functions). Machine Learning: Scikit-learn, TensorFlow, PyTorch, Azure ML, AWS Bedrock,Time Series Forecasting

(Prophet, LSTM, ARIMA).

Experimentation & Analytics: A/B Testing, Chi-Square Tests, T-Tests, Hypothesis Testing, Statistical Analysis, Feature Engineering.

Development & Version Control: Git, GitHub, JIRA, Streamlit, Flask. Education

University of North Carolina at Charlotte August 2023 – May 2025 Master of Science in Data Science & Business Analytics Charlotte, North Carolina Projects

23XI Racing Merchandise Analysis - Fan Profiling & Campaign Optimization

• Segmented using clustering (Python) and built a Tableau dashboard, enabling personalized campaigns that boosted CTR by 18%.

• Identified top-spending fan cohorts, leading to a 12% increase in merchandise revenue through targeted promotions. Customer Retention - CLTV & Churn Prediction (Telecom)

• Predicted churn with accuracy (Random Forest) and identified high-CLTV users, reducing simulated churn via retention incentives.

• Automated retention reporting in Power BI, saving 10+ hours/week in manual analysis for the marketing team. Cricket Legends Dashboard - Performance & Engagement Analytics

• Analyzed 5+ years of player/fan data (SQL, Python) to create a public Tableau dashboard, driving higher social media engagement.

• Mapped fan journey drop-offs, leading to optimized content scheduling and longer session durations.

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