Hello, I'm
Laurentiu Mandocescu
A Master's Student in Business Analytics with expertise in machine learning and database technologies. I combine business acumen with technical versatility to transform complex data into actionable insights, adapting quickly to new technologies and challenges.
Interested in my athletic background?About Me
I am a dedicated Master's student in Business Analytics at DePaul University with a strong foundation in data science and software development. My academic journey has equipped me with expertise in statistical analysis, data visualization, and predictive modeling using R, Python, SQL, and Tableau.
My Master's program has introduced me to advanced machine learning models and large language models, areas I'm passionate about and continuously exploring. I stay up-to-date with the latest developments in AI and data science, applying these cutting-edge technologies to solve complex business problems.
Currently working as a Graduate Assistant at DePaul University's Office of the President, I leverage end-to-end data science workflows to develop interactive dashboards and data-driven insights that support strategic decision-making across multiple departments.
My unique educational background combines a Bachelor's in Business Administration with a minor in Computer Science, giving me both the business acumen to understand organizational needs and the technical skills to implement effective solutions. This interdisciplinary approach has expanded my technical stack to include Java, C++, Python programming, and database technologies like PostgreSQL and Supabase.
I'm a quick learner who thrives on tackling new challenges and mastering unfamiliar technologies. Whether it's front-end development with React and TypeScript, back-end systems with Node.js, database management, or data analysis with Python and R, I'm eager to expand my skill set and take on projects of varying scopes and complexities.
Work Experience
Graduate Assistant - Data Science
September 2023 – PresentDePaul University Office of the President
- Leveraged end-to-end data workflows (including data ingestion and wrangling) using R, Python, and Tableau to develop interactive dashboards and data-driven insights that support strategic decision-making across multiple departments.
- Collaborated on a research paper assessing U.S. News & World Report ranking methodologies to provide data-driven recommendations and strategic insights for improving the University's standing in national rankings.
- Implemented advanced analytics and machine learning approaches (e.g., regression, spline calibration) alongside data preprocessing steps (including normalization) and data ingestion workflows, enabling robust predictive models and strategic insights for university ranking improvements.
- Co-developed a Tableau dashboard in collaboration with a cross-functional teammate, integrating data from multiple departments (via SQL) to support the Board of Trustees in making data-driven decisions on financial health, retention, enrollment, admissions, and faculty trends.
- Led feedback sessions with stakeholders to optimize product delivery by refining UI/UX design, resulting in clearer data presentation and an enhanced user experience.
Data Scientist
February 2025 – PresentSigma Art Division (Chicago, IL)
- Spearheaded outreach data tracking by collecting and analyzing performance metrics across LinkedIn, Upwork, and other freelance platforms, helping optimize client acquisition strategies and improve conversion rates.
- Collaborated with cross-functional client teams to define project scopes, gather requirements, and present findings using clear visualizations and storytelling via Excel and PowerPoint.
- Contributed to building the company's online presence by developing website components using Readymag and custom React elements, enhancing user experience and showcasing service offerings to attract new clients.
Personal Projects
US News & World Report Ranking Simulator
Co-authored research with Ammar Alghamdi that successfully replicated and calibrated the USNWR National Universities ranking system using a two-stage approach: weighted composite scoring followed by smoothing spline calibration. Compared three calibration strategies (smoothing spline, PCR, and Elastic Net) to accurately predict university rankings and identify key strategic improvement areas.
Relevant Coursework
Credit Application Prediction
Applied data preprocessing techniques, dimensionality reduction with PCA, and SVM classification. Demonstrated how proper feature engineering significantly improves model performance and interpretability.
TransitCard System
Implemented an object-oriented Python class for a public transit card with balance management, ride validation, and transaction limits. Demonstrates encapsulation, error handling, and proper testing.
Voter Behavior Analysis
Developed and optimized machine learning models for classification and regression problems. Implemented feature selection, cross-validation, and hyperparameter tuning.
UCI Datasets Classification
Implemented and compared KNN and Random Forest classification methods on the UCI Glass and Wine datasets. Explored parameter optimization and feature importance analysis.
Academics
Master of Science in Business Analytics
GPA: 3.94/4.00Bachelor of Science in Business Administration
GPA: 3.86/4.00Contact Me
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Location
Chicago, IL