Data Analyst

Sabria Joyner

Charlotte, NC 704-***-**** ******.******@*******.*** LinkedIn

PROFESSIONAL SUMMARY

Detail-oriented data analyst with 8+ years of experience in project coordination, data reporting, and cross-functional communication. Skilled in SQL, SAS, Python, and R with a strong foundation in predictive modeling, classification, and data visualization. Pursuing an MS in Data Analytics specializing in AI & Machine Learning (GPA: 3.90). SKILLS

Document Management & Data Entry: Microsoft Word, Excel, Outlook, PowerPoint Data Analytics & Programming: SQL, R, SAS, Python

Data Visualization & Reporting: Excel, SAS Studio, RStudio, Power BI, Tableau Data Mining & Predictive Analytics: SAS Enterprise Miner, Machine Learning CERTIFICATES

SAS - CSU Global Academic Specialization in Predictive Analytics Management (Credly Badge) Deloitte Australia Data Analytics Job Simulation on Forage - May 2025 (Certificate)

• Simulated client project using Excel and Tableau for data cleaning and validation WORK EXPERIENCE

Turing (Contract) Charlotte, NC

Business Analyst (Audio Trainer) May 2025

• Contributed to the fine-tuning and evaluation of large language models (LLMs) by recording high-quality audio prompts, adhering to detailed linguistic and task guidelines.

• Completed over 700 assignments to support model training by enhancing the clarity, precision, and factual accuracy of AI-generated outputs.

• Helped advance model performance by providing structured, prompt-based feedback to enhance audio comprehension and natural language processing (NLP).

JPMorgan Chase (Contract) Charlotte, NC

IRS Mail Extraction Mar 2025 - May 2025

• Handled high volumes of federal tax returns, payments, and sensitive documents with accuracy and confidentiality while meeting overnight deadlines.

• Supported back-office financial operations to ensure timely processing and operational continuity during peak tax season.

General Dynamics NASSCO Everett, WA

Sr Program Analyst Nov 2021 - Oct 2023

• Analyzed large datasets and maintained databases to support executive decision-making and deliverables across multiple shipyard projects, directly supporting the project management team & key stakeholders.

• Facilitated communication between cross-functional teams, leadership, and external stakeholders to manage project scope, resources, and reporting timelines.

• Built status reports in Excel (PivotTables, VLOOKUPs, modified formulas) to track milestones and performance trends for weekly production review briefs with the commanding officer and senior government officials.

• Issued escalation reports and responded to inquiries from managers in high-pressure environments, maintaining project momentum and professionalism.

• Prepared and presented executive-level reports and briefings, summarizing KPIs, risks, and recommendations for process improvements.

US Navy Norfolk, VA

Damage Controlman, Petty Officer First Class (Work Center Supervisor) Oct 2014 - Jan 2021

• Supervised teams of up to 30 personnel in high-stakes environments, overseeing critical emergency response and maintenance operations for damage control systems.

• Implemented damage control training programs for over 5,000 personnel using PowerPoint and hands-on instruction; leveraged Excel with PivotTables to track completion rates, identify gaps, and improve defense readiness.

• Communicated across departments and ranks to manage projects related to safety inspections, equipment maintenance, and emergency drills, ensuring alignment with mission objectives

• Tracked progress of operational initiatives, proactively identifying risks, adjusting schedules, and ensuring project objectives were consistently achieved under tight deadlines. EDUCATION

Colorado State University Global Denver, Colorado

• Master of Science in Data Analytics: Artificial Intelligence & Machine Learning in progress, Dec 2025 Specialization

• Bachelor of Science in Human Resource Management PROJECTS (ANALYTICS & DATA SCIENCE): FEB 2024 - PRESENT Credit Risk Classification Model – German Credit Dataset Built a logistic regression model in SAS to classify loan applicants as good or bad credit risks:

• Cleaned and transformed data; partitioned dataset using a 60/40 training/validation split

• Evaluated model performance using confusion matrix, odds ratios, and lift chart to assess predictive accuracy Employee Attrition Prediction – IBM HR Dataset

Developed classification models in SAS Enterprise Miner to identify key drivers of employee attrition:

• Trained decision tree and neural network models; compared performance using misclassification rate and lift chart

• Interpreted variable importance and node splits to guide HR retention strategy Relational Database Management System (RDBMS) Design – Johnson Video Store Database Designed a relational database to centralize video rental operations and replace scattered Excel files:

• Developed normalized schema to support efficient tracking of rentals, customers, and inventory

• Wrote SQL queries to extract insights into customer behavior, rental frequency, and inventory trends Exploratory Data Analysis – Jupyter Notebook (Python) Performed data cleaning and visualization using Python through coursework and hands-on projects:

• Applied pandas for data wrangling, handling missing values, and preparing datasets for analysis

• Created clear visualizations using matplotlib to explore trends, patterns, and data quality issues Time Series Decomposition – Quarterly Revenue Data Analyzed seasonal and trend components of revenue data using linear regression-based decomposition in R:

• Modeled additive seasonality using lm and dummy variables; visualized trend and seasonality with ggplot2

• Interpreted decomposed components to evaluate seasonality and forecast business trends

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