Data Analyst Business Intelligence

Navya Teja Pathuri

Charlotte, NC +1-704-***-**** ********@*********.***

SUMMARY

Data Analyst with 2+ years of experience in business intelligence and data analytics. Proficient in SQL, Python, and Excel, with a keen ability to transform and interpret complex data for actionable insights. Demonstrated expertise in ETL development, statistical modeling, and dashboard creation to optimize data workflows and support strategic decision-making. EDUCATION

University of North Carolina at Charlotte (UNCC) Aug 2023 - May 2025 Master's, Data Science and Business Analytics

SRM University Aug 2019 - Jun 2023

Bachelor of Technology, Electronics and Communication EXPERIENCE

University of North Carolina at Charlotte Research Analyst Aug 2023 - Present Analyzed NFL and NHL player performance data using statistical modeling techniques to evaluate key metrics such as Points Shares (PS), Time on Ice (TOI), Games Played (GP), and Approximate Value (AV), ensuring data accuracy and supporting trend identification in career progression.

• Conducted thorough Exploratory Data Analysis (EDA) on performance indicators to identify trends and position-based variations across both sports.

• Developed and implemented data imputation strategies, ensuring complete datasets for robust statistical modeling and effective data cleaning.

• Utilized visualization tools including Matplotlib, Seaborn, and Tableau to create dynamic reports that enabled stakeholders to interpret complex data trends.

• Applied advanced statistical models, including splines and curve-fitting techniques, to predict long-term player performance, validating model accuracy using rigorous statistical validation methods.

• Documented comprehensive research methodologies and data processing techniques in a GitHub repository, facilitating reproducibility and transparency in data analysis.

• Compiled detailed research reports outlining methodologies, key insights, and recommendations for scouting, player evaluation, and future predictive analytics in sports.

Around Me Data Analyst Jan 2022 - Jul 2023

• Implemented Tableau reports to quantify the effect of doubled rewards on in-game currency and key performance indicators such as player progression, retention, engagement rates, and time to level up.

• Engineered real-time dashboards and designed A/B testing models to provide actionable insights and recommendations to Product Managers, effectively communicating analytical findings.

• Utilized Excel functions including VLOOKUP, data validation, Power Query, and pivot tables to automate reporting and streamline data visualization, aligning with efficient data analytics strategies.

• Designed statistically sound A/B testing experiments using Chi-square and T-tests, ensuring results were significant at a 95% confidence level for product testing initiatives.

• Developed Tableau dashboards for marketing campaign analytics from Snowflake data, focusing on KPIs such as open rate, click-through rate, bounce rate, and revenue per click.

• Created customer clusters using KNN on the Customer Data Platform (Blue Conic) to target ads effectively, achieving an average ad conversion rate of 10-12% and generating estimated revenue of $380,000.

• Collaborated with sales teams to implement ETL pipelines integrating Snowflake and CRM data, optimizing customer outreach and enhancing segmentation techniques.

• Transformed utility data from 15-minute intervals to hourly aggregates using Python and SQL, applying data normalization to consolidate and streamline data across extensive tables.

SKILLS

• Languages: Python, R, SQL, PL/SQL, NoSQL

• Cloud Technologies: AWS (S3, IAM, EC2, quick Sight, Athena, Glue, Redshift, Lambda, Sage maker), GCP (Big query, Looker, Crone jobs)

• ETL, Visualization Tools: Tableau, Power BI, Excel

• Database: MySQL, PostgreSQL, Oracle, MongoDB, Snowflake, Amazon RDS

• Libraries: NumPy, Pandas, Matplotlib, SciPy, Scikit-learn, Seaborn, TensorFlow, Ggplot2, PySpark

• Machine Learning: Linear Regression, Logistic Regression, Decision Trees, Supervised Learning, Unsupervised Learning, Classifica- tion, SVM, Random Forests, Naive Bayes, KNN, K-Means, CNN, Statistics

• Other Skills And Tools: Toad, JIRA, Data Structures, Microsoft Office, Git, Data Cleaning, Data Warehousing, Data Wrangling

• Operating Systems: Windows, MacOS

• Data Analysis: Data Analysis, Data Modeling, Web Scraping, Data Mining

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