Data Analyst Machine Learning
Resume:
Sandy, Utah - ***** SAI GOWTHAM YANALA
*******.***@*****.***
linkedin.com/in/gowtham-yanala
PROFESSIONAL SUMMARY:
Associate Data Analyst with 5+ years of experience in ETL, SQL optimization, data analytics, and business intelligence. Proficient in Azure Data Factory, Python, Power BI, and AWS to automate reporting, optimize data pipelines, and enhance data-driven decision-making. Passionate about leveraging machine learning & predictive analytics to drive business impact. Strong expertise in data governance, compliance, and financial reporting. EDUCATION
Salt Lake City, Utah University of Utah August 2022- August 2023
• Master’s in information systems- MIS with Business Analytics Track
• Graduate Coursework: Intro to Business Analytics, Data Visualization, Statistics and Predictive Analytics, Data Mining, Data Science and Big Data Analytics, Data Warehousing Design and Implementation, Advanced Data Management. Hyderabad, India CMR Technical Campus June 2015 – July 2019
• B.Tech. in Computer Science & Engineering
• Undergraduate Coursework: Operating Systems, Database Theory and Design, Algorithms, Programming Languages, Advanced Data Structures, Excel, Design & Analysis Algorithm, Web Technologies, Systems Analysis & Design. LANGUAGES, KEY SKILLS AND TECHNOLOGIES
• Languages/Libraries: Java, SQL, C, Python (pandas, seaborn, matplotlib, TensorFlow, NLTK, Scikit-learn, Numpy, OpenCV), R (dplyr, ggplot, caret), Unix Bash Scripting, Natural Language Processing, Deep Learning.
• Databases: SQL server, My SQL, Postgres SQL, Oracle, NoSQL, Dynamo DB, Redshift, Netsuite.
• Tools: AWS S3, EC2, Apache Airflow, Apache Spark, Hadoop, Git, Domo, Tableau, Power BI, Jupyter, Docker, PyCharm.
• Machine Learning: Linear Regression, Logistic Regression, Decision Trees, Classification model, k-nearest algorithm,
• Statistics & Others: Descriptive Modelling, Predictive Modelling, Linear Modelling, Cross-Validation, Inference, Web Scraping, Text Analytics, Time Series Forecasting, Hypothesis Testing.
• Certifications: PL-300: Microsoft Power BI Data Analyst, Graduate Certificate in Business Analytics. EMPLOYMENT
Associate Data Analyst Bridge Investment Group, Salt Lake City, Utah August 2024 – Present
• Automated an end-to-end ETL pipeline from SharePoint to Azure Blob Storage and back to SharePoint using Azure Data Factory, SQL stored procedures, and Power Automate, reducing manual data handling by 70%.
• Designed & implemented advanced SQL data transformation workflows, ensuring data cleaning, formatting, and aggregation aligned with business rules, leading to a 30% improvement in reporting accuracy.
• Developed interactive Power BI dashboards using advanced DAX and data modeling, enabling real-time insights and reducing report processing time by 40%.
• Optimized backend reporting for Yardi by crafting complex SQL queries (stored procedures, CTEs, Temp Tables, Subqueries, and Joins), enhancing financial reporting efficiency by 35%.
• Automated file transfers from Azure Blob Storage to SharePoint using Power Automate, ensuring seamless integration and maintaining an organized directory structure for end-user access.
• Collaborated with cross-functional teams to ensure data quality, integrity, and alignment with business requirements, translating complex datasets into actionable insights for stakeholders.
• Developed & maintained scalable, automated, and user-friendly systems, reports, and dashboards, improving workflow automation and data accessibility.
• Conducted rigorous unit testing & validation post-deployment to ensure data accuracy and reliability, reducing post- production errors by 25%.
Data Analyst Zetabit Solutions, Remote, USA January 2023 – July 2024
• Designed & implemented a fully automated data pipeline using Azure Data Factory (ADF) to ingest, transform, and load FTP data into a SQL database, reducing manual data handling by 60%.
• Developed forecasting models using Time Series Analysis, SQL, and Python, accurately predicting trends in solar energy financials (Budget, Actual, Proforma) and ERCOT battery performance, improving forecasting accuracy by 25%.
• Built interactive dashboards in Tableau, utilizing context filters and data blending to provide real-time insights into energy production & costs, leading to a 30% improvement in decision-making efficiency.
• Optimized ETL processes, implementing SQL-based data merging strategies, reducing data duplication and increasing processing efficiency by 40%.
• Led full project lifecycle management, collaborating with stakeholders, defining Service Level Objectives (SLOs), tracking tasks in JIRA, and ensuring data quality through validation & testing, resulting in a 99% accuracy rate. Data Analyst, Capstone State of Utah, Department of Commerce August 2022– August 2023
• Engineered and maintained scalable data pipelines using Azure Data Factory, ensuring real-time data integration and enhancing data processing speed by 40%.
• Utilized advanced SQL techniques to identify and resolve data inconsistencies across multiple sources, improving data quality compliance by 30%.
• Automated ETL workflows using Python and Azure Databricks, streamlining data transformation processes and reducing manual efforts by 50%.
• Collaborated with cross-functional teams to diagnose and resolve data-related challenges, ensuring seamless real- time data processing with minimal downtime.
• Communicated complex data insights to key stakeholders, aligning data architecture with business intelligence and reporting needs, resulting in improved decision-making efficiency. Data Quality Specialist Amazon Development Centre, India August 2020 – July 2022
• Optimized SQL queries on Amazon Redshift & PostgreSQL, reducing query execution time by 35%, enabling faster analytics for supply chain performance tracking.
• Developed predictive models using Python (scikit-learn, XGBoost, Time Series Forecasting) to anticipate seasonal demand fluctuations, improving inventory planning accuracy by 20%.
• Designed & maintained automated reporting solutions using AWS (S3, Lambda, QuickSight), reducing manual reporting efforts by 50% and enabling real-time supply chain insights.
• Analyzed fulfillment center efficiency, identifying bottlenecks in inventory movement, leading to a 10% reduction in order processing delays through data-driven optimization.
• Built end-to-end data pipelines & dashboards to track KPIs such as stock turnover, lead times, and warehouse utilization, helping stakeholders make data-driven logistics decisions. Software Engineer, Data One Kitchen Company, India August 2019 – July 2020
• Developed & optimized REST API endpoints to enable real-time data integration, improving system interconnectivity and response time by 30%.
• Deployed applications on Azure, leveraging Azure Data Factory & Azure Databricks for seamless data transformation
& processing, reducing manual data handling by 40%.
• Built scalable real-time data pipelines using Azure Data Lake, Functions, and Event Hubs, enhancing data flow efficiency by 35%.
• Established end-to-end CI/CD pipelines via Azure DevOps, ensuring automated testing, streamlined deployments, and 99% uptime.
• Implemented Infrastructure as Code (IaC) methodologies to automate provisioning & scaling of Azure resources, optimizing project workflows & reducing deployment time by 50%. Big Data Developer, Intern Open Hardware Days Pvt.Ltd May 2018 – July 2018
• Stored millions of health records in the Hadoop distributed file system (HDFS) and analyzed them using 2 processes like mapper and reducer, to help understand hospitality growth in different locations.
• As a Hadoop developer, I assisted in discovering valuable decisions by analyzing data patterns with HIVE tools.
• Provided a comprehensive overview of big data analytics in healthcare and other systems that allow the government to deliver 80% of its value-added services to citizens. INDEPENDENT PROJECTS
Health Care Analysis Using Smart Meter Data Analysis Jan 2019 – April 2019
• Objective/Description: The application monitors human activities and appliances usage with a smart meter to predict health problems using 3 techniques - Cluster analysis, Frequent patterns, and prediction processes.
• Paper publication: INTERNATIONAL JOURNAL FOR SCIENTIFIC RESEARCH & DEVELOPMENT
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