Junior Machine Learning Engineer / BI Analyst Resume Spencer Nash Junior Machine Learning Engineer / BI Analyst (919) 555-0184 spencer.nash.analytics@example.com linkedin.com/example/spencernash Raleigh, NC 27606 STRENGTHS Analytical judgment Turned ambiguous banking questions into validated datasets and dashboards; faculty reviewers trusted clear reasoning behind each result. Practical automation Replaced repeated notebook steps with Python and pandas scripts; peers gained a smoother weekly review routine. Clear explanation Presented model errors and fairness concerns in plain language; thoughtful discussion improved research decisions before evaluation. Reliable delivery Used Docker, tests, Git, and documentation on shared projects; teammates viewed repositories as ready for practical review. Stakeholder focus Started with five stakeholder questions before building Tableau views; resulting dashboards supported focused budgeting conversations. SKILLS Analysis Skills Artificial Intelligence Automation Banking Services Business Intelligence Cloud Computing Data Analysis Data Science DevOps Java LinkedIn Machine Learning Python Software Engineering SQL LANGUAGES English Native 40 Spanish Intermediate 20 MY CAREER 1.8 Years Machine Learning Engineering Research Assistant at University Machine Learning Lab (1.1 Years) Junior BI Analyst, Academic Capstone at Capstone Business Intelligence Project (4 Months) Python/Java Developer, University Project at Software Engineering and Cloud Automation Project (4 Months) SUMMARY Junior machine learning engineer and BI analyst with two years of applied academic experience building Python models, SQL reporting workflows, and cloud-ready data solutions. Computer science training spans machine learning, artificial intelligence, data analysis , business intelligence , software engineering , automation , DevOps, and database design. Delivered supervised banking-services and budgeting projects that turned stakeholder questions into documented datasets, dashboards, and predictive prototypes. Comfortable with Python, Java, SQL, pandas, scikit-learn, Tableau, Git, Docker, AWS, REST APIs, and PostgreSQL. Practical work covers DSA, system design, SQL, model evaluation, pipeline automation, technical documentation, and behavioral storytelling. Ready to bring curiosity, steady execution, and thoughtful communication to a team building dependable software, analytics, and ML solutions. EDUCATION Bachelor's Degree in Computer Science North Carolina State University GPA: 3.8 2026 Raleigh, NC Coursework: Machine Learning, Data Analysis, Business Intelligence, Software Engineering, Database Design TECHNICAL SKILLS Programming Languages: Python, Java, SQL Machine Learning: scikit-learn, Model Evaluation, Classification Data Analysis: pandas, Data Profiling, Forecasting Business Intelligence: Tableau, Dashboards, Calculated Fields Cloud Platforms: AWS, AWS Academy Cloud Foundations, Cloud Computing DevOps Tools: Docker, GitHub Actions, Git Databases: PostgreSQL, Star Schema, SQL Queries Software Engineering: REST APIs, Unit Testing, Structured Logging Automation: Python Scripts, CI Pipelines, Build Checks Data Structures: DSA, Algorithms, Complexity Analysis System Design: Service Design, Integration Patterns, Scalability Documentation: README Files, Model Cards, Technical Guides SKILLS Analysis Skills Artificial Intelligence Automation Banking Services Business Intelligence Cloud Computing Data Analysis Data Science DevOps Java LinkedIn Machine Learning Python Software Engineering SQL EXPERIENCE Machine Learning Engineering Research Assistant University Machine Learning Lab August 2025 - Present Raleigh, NC Faculty-guided research role supporting supervised machine learning , reproducible experiments, data preparation, model evaluation, Docker delivery, and clear technical communication for banking-services analysis. Built Python classification pipeline for banking-services data with reproducible experiment notes and clean feature preparation. Compared logistic regression, random forest, and gradient boosting through precision, recall, F1, and confusion matrices. Automated pandas data preparation scripts, shortening weekly experiment setup and improving review consistency for researchers. Containerized prototype with Docker and documented dependencies, configuration, and local execution for four-person research team. Presented model assumptions, error patterns, and fairness considerations during lab reviews for timely faculty feedback. Published repository with SQL extracts, model cards, test cases, and README supporting professional ML documentation. Junior BI Analyst, Academic Capstone Capstone Business Intelligence Project January 2025 - May 2025 Raleigh, NC Business intelligence role delivering SQL analysis, Tableau reporting, Python trend analysis, and documented recommendations for simulated banking budgeting and branch right-sizing decisions. Designed banking intelligence solution linking branch budgeting , service demand, account activity, and right-sizing decisions. Wrote SQL against star-schema warehouse with 180,000 anonymized records and validated reconciliation totals. Created Tableau dashboards covering budget variance, service volume, account activity, and branch comparisons for stakeholders. Profiled seasonal trends with Python and pandas, producing documented forecasting inputs for budgeting workshops. Translated five stakeholder questions into dashboard requirements, wireframes, calculated fields, and acceptance checks. Delivered recorded presentation and implementation guide earning top-tier evaluation for clarity, traceability, and decision usefulness. Python/Java Developer, University Project Software Engineering and Cloud Automation Project August 2024 - December 2024 Raleigh, NC Software engineering role delivering a Java and Python service prototype with REST integration, PostgreSQL, automated testing, Docker Compose, and GitHub Actions for a simulated operations workflow. Developed Java and Python service ingesting support events and exposing summary metrics for business intelligence . Implemented REST endpoints, validation rules, structured logging, and unit tests within a shared codebase. Configured GitHub Actions for tests, linting, and build checks on every repository change. Connected application with PostgreSQL through Docker Compose and documented environment setup for peer evaluators. Applied SQL aggregation and Python analysis to identify backlog patterns for an operations review. Explained design tradeoffs, failure handling, deployment steps, and ML opportunities during department showcase. PROJECTS Banking Services Risk Classifier 2026 Built a documented Python and scikit-learn prototype for imbalanced account-risk analysis. Compared models, recorded evaluation results, and presented fairness considerations in a professional review format. Branch Budget Intelligence Dashboard 2025 Created SQL and Tableau reporting for simulated bank branches. Connected budget variance, service demand, and operational right-sizing views so finance stakeholders could discuss decisions with shared evidence. Cloud Operations Event Service 2024 Developed Java and Python REST services with PostgreSQL, Docker Compose, GitHub Actions, logging, and tests. Project demonstrated deployable software engineering habits beyond classroom exercises. PORTFOLIO Title: Professional Project Repository Link: linkedin.com/example/spencernash Description: Selected ML, BI, Java, Python, and cloud automation work presented through documented project evidence. LEADERSHIP & AWARDS Dean's List, North Carolina State University, Fall 2024 and Spring 2025 Best Applied Analytics Presentation, College Capstone Showcase, 2025 Undergraduate Research Poster Finalist, North Carolina State University, 2026 CERTIFICATIONS Google Data Analytics Professional Certificate 2025 AWS Academy Cloud Foundations 2025 Machine Learning with Python, IBM SkillsBuild 2026 PROFESSIONAL AFFILIATIONS Machine Learning Lab Peer Mentor, North Carolina State University, 2025-2026 Treasurer, Computer Science Student Association, 2024-2025 Volunteer Workshop Presenter, Data and Analytics Student Group, 2025 LANGUAGES English (Native) Spanish (Intermediate) ADDITIONAL INFORMATION Work Status : Authorized to work in United States. No sponsorship required. ADDITIONAL INFORMATION Work Status : Authorized to work in United States. No sponsorship required. REFERENCES AVAILABLE ON REQUEST
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