Data Science Engineer

SAI CHARAN TAMMINENI

Dallas, TX *******@*******.*** +1-925-***-**** LinkedIn

EDUCATION

Oklahoma State University – Spears School of Business Stillwater, OK Master of Science, Business Analytics and Data Science (GPA: 3.71/ 4) Aug 2023 – May 2024 Courses: Statistics for Data Science, Predictive Analytics, Categorical Data Analysis, Data Wrangling Nitte Meenakshi Institute of Technology (Visvesvaraya Technological University) Bangalore, India Bachelor of Engineering, Electronics and Communication (GPA: 3.85 / 4) Aug 2016 – Aug 2020 WORK EXPERIENCE

Verint Systems Atlanta, GA (Remote)

Data Engineer May 2024 – Dec 2024

• Designed and executed 50+ ETL and ELT workflows using Informatica Intelligent Cloud Services (IICS), improving data pipeline efficiency by 30%

• Improved query performance by 25% for the Marketing team’s data, using advanced SQL techniques like Window Functions, CTEs, and indexing, which sped up processing in SQL Server and Oracle SQL Developer

• Developed and deployed Views and Stored Procedures to the Data Warehouse, optimizing data retrieval, streamlining maintenance, and driving improvements in application efficiency within Microsoft Azure

• Enhanced data accuracy by 15% and reduced preparation time by 20% using Power BI Dataflows to cleanse and integrate data from multiple sources

• Extracted and integrated data from Cornerstone APIs using postman into EDW (Enterprise Data Warehouse), accelerating access to critical insights by 20% and enhancing decision-making efficiency CGI Bangalore, India

Associate Business Analyst Mar 2021 – Jul 2023

• Executed A/B tests on CalSTRS’ retirement website, leveraging data-driven insights to refine user experience and boost customer satisfaction by 10%

• Monitored and optimized SQL Server databases supporting Microsoft Dynamics AX and D365, improving query performance by fine-tuning indexes, managing database size, and ensuring optimal disk space utilization

• Built SQL-driven analytics solutions to process and analyze diverse retirement schemes data, resolving 95% of CalSTRS user issues by ensuring accurate member benefit calculations for cross-functional teams

• Extracted and analyzed financial metrics from 10M+ transactions using SQL and automated reporting with Excel VBA, improving forecasting accuracy and financial reporting efficiency.

• Developed interactive Power BI dashboards, visualizing retirement contributions, pension fund trends, and financial risk assessments to support decision-making for executives SKILLS

Business Transformation Frameworks — Organizational Change Management, Agile Methodologies (Scrum, Kanban), Business Process Re-engineering, Stakeholder Management, Business Requirements Gathering, Gap Analysis, Technical Documentation, PowerPoint Presentation

Technical Skills — SQL, Python, R, Data Analysis & Visualization, Forecasting & Predictive Analytics, Pricing & Promotion Optimization, Business Intelligence & Reporting, ETL & Data Warehousing, Statistical Modeling Software Tools — Dynamics AX ERP, Informatica, Google Cloud Platform (GCP), AWS, Azure, Snowflake, Power BI, Tableau, Microsoft Excel, Alteryx, JIRA, ServiceNow Soft Skills — Cross-functional Collaboration, Problem-Solving, Communication & Presentation, Self-Starter, Teamwork

& Stakeholder Management, Stakeholder Management, Adaptability, Teamwork & Leadership, Process Improvement ACADEMIC PROJECT EXPERIENCE

• Optimized Trucking Routes for Groendyke: Spearheaded a year-long project using Tableau to reduce round-trip distances by 15%, improve efficiency, and enhance truck drivers' work-life balance by 20% through strategic drop-off and pick-up location identification.

• Love's Macro Space Optimization Case Competition: Boosted profitability by 25% in two remodeling stores through data-driven macro space allocation, utilizing Tableau for visualizations, SQL Server for data transformation, and A/B testing to identify key patterns

• Breast Cancer Detection Analysis: Conducted data-driven analysis on tumor classification using statistical modeling and machine learning techniques. Leveraged logistic regression to identify key predictors, achieving 94% accuracy. Provided actionable insights through data visualization and reporting to support clinical decision-making.

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