Data Analyst Software Engineer

Neil Patel

v USA Permanent Resident +1-551-***-**** § GitHub ï LinkedIn # *********.****@*****.*** Summary

Detail-oriented Data Analyst with 2+ years of experience in data analysis, data visualization, and reporting. Proficient in SQL, Google BigQuery, Excel, and Tableau. Skilled in data cleaning, statistical analysis, and business insights, with a strong foundation in data modeling and data-driven decision making. Education

Kent State University Master of Science in Computer Science Jan 2023 – Aug 2024 Gujarat Technological University Bachelor of Science in Computer Engineering Jun 2018 – Jun 2022 Professional Experience

Software Engineer Kent State University Jan 2023 – Jul 2024

• Spearheaded the development of five new interactive features for the web application using React and AWS; enhancements led to a 27% increase in user engagement and reduced load times by 33%.

• Designed and executed a data backup strategy utilizing Python and PostgreSQL; this approach ensures daily backups of 1TB of data, maintaining data integrity and security for critical business operations.

• Created detailed technical documentation for new software features implemented on university server; this initiative enhanced team onboarding process for junior developers, cutting down training time from two weeks to just four days. Data Analyst Crucial Software and IT Park Pvt. Ltd. Jan 2021 – Dec 2022

• Designed and launched a sophisticated data visualization dashboard using Tableau and Power BI, boosting data interpretation accuracy and driving a 20% improvement in strategic insights for stakeholders.

• Executed data extraction and transformation processes using SQL, enhancing the accuracy of sales forecasts; improved forecasting accuracy by 23% while reducing manual reporting efforts by approximately 10 hours each week.

• Spearheaded collaboration with cross-functional teams to define 15 key performance indicators (KPIs) and develop a robust metrics framework; facilitated data-driven decision-making that enhanced operational efficiency across departments. Data Science Intern LetsGrowMore Jan 2021 – Jun 2021

• Analyzed large datasets comprising over 5 million entries to identify critical user behavior trends; insights directly influenced the development of three new product features, improving user engagement.

• Led a project to integrate machine learning algorithms into demand forecasting, enhancing predictive accuracy by 40%; the model processed over 500,000 data points monthly to inform inventory decisions.

• Created a machine learning model with Python to predict customer behavior based on historical data, achieving over 93% accuracy; this insight directly contributed to designing targeted marketing strategies within two months. Skills

Programming Languages: Python, Java, R, SQL, Javascript. Tools and Frameworks: Tableau, Power BI, Django, Angular, ElasticSearch, Flask, REST APIs, Docker, Kubernetes, CI/CD, Amplitude, Apache Kafka, Flink, Spark, Apache Airflow, Snowflake, Hadoop, Hive. Cloud Services and Database: AWS, Azure, GCP, PostgreSQL, Cassandra, NoSQL, MongoDB. Projects

Pharmaceutical Sales Analysis Power BI Desktop,, Tableau, Power Query Editor 2 Mar 2024 – Apr 2024

• Developed comprehensive Power BI dashboards to analyze and visualize sales data, providing insights into sales performance by region, product, and sales team, which led to a 20% improvement in sales forecasting accuracy.

• Implemented data transformation and modeling using Power Query Editor and Power BI Desktop, creating a star schema data model to enable efficient multi-dimensional analysis, reducing data processing time by 30%.

• Created a series of interactive reports that delivered actionable insights into distributor, customer, and team performance; tailored to spotlight 10 key metrics and trends, facilitating optimization of sales strategies and decision-making. Customer Behavior Analytics AWS S3, AWS Redshift, EMR, Spark, Quicksight Mar 2024 – Apr 2024

• Engineered a data pipeline leveraging AWS services such as S3, Redshift, and EMR alongside Apache Spark for processing large datasets; delivered actionable insights that improved understanding of customer behavior and purchase patterns.

• Designed and implemented robust ETL processes using Apache Airflow and PySpark, extracting data from 5+ sources, transforming it for high accuracy, enabling real-time analytics that informed critical marketing strategies.

• Created a series of comprehensive dashboards using AWS QuickSight to provide insights into consumer behavior trends; findings directly addressed three critical factors affecting abandoned carts in e-commerce operations. Certification

Google Data Analytics Professional Certification 2 Nov 2023

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