Data Science Intern - Workforce & Analytics

MIRIAM MASHAVA

Jersey City, New Jersey ********@****.*** 917-***-**** LinkedIn

PROFILE

Data science graduate student with more than two years of experience analyzing large operational datasets, building dashboards, improving data quality, and translating complex findings into practical reporting. Skilled in Power BI, Tableau, Python, SQL, R, statistical analysis, and cross- functional problem solving, with a strong interest in workforce analytics and mission-driven decision-making. EDUCATION

M.S. in Data Science Pace University Expected Dec 2026 Coursework: Data Mining, Machine Learning, Practical Data Science, Scalable Databases, Algorithms for Data Science B.Sc. in Operations Research and Statistics National University of Science and Technology, Zimbabwe Nov 2022 EXPERIENCE

Senior Statistician Simbisa Brands Ltd Sep 2022 - Dec 2024

Analyzed high-volume sales, payment, inventory, and operational data using Python, R, SQL, SPSS, and Excel to identify trends, outliers, reporting inconsistencies, and performance drivers across branches.

Built Power BI and Tableau dashboards and recurring reports that gave management clearer visibility into KPIs, exceptions, and changes over time.

Designed reconciliation and data-validation workflows across Finance, Operations, Internal Audit, and IT sources, tracing inconsistencies to underlying records and improving the reliability of management reporting.

Applied statistical modeling, time-series forecasting, and exception analysis to investigate changing patterns and translate findings into practical recommendations for business teams.

Worked with technical and nontechnical stakeholders to clarify reporting needs, document analytical findings, and communicate results in a clear, usable form.

PROJECTS

FraudGuard AI: Drift-Aware and Explainable Fraud Detection May 2026 - Present

Developing a model-monitoring framework with NannyML and SHAP to detect concept drift, explain changes in model behavior, and support reliable ongoing analytics.

Financial Transaction Fraud Detection Feb 2026 - Apr 2026

Built an end-to-end anomaly-detection pipeline for 216,000+ financial transactions; engineered behavioral and time-based features and evaluated GMM and Isolation Forest using ROC-AUC, PR-AUC, precision, recall, and F1-score. Lloyds Banking Group UX Design Job Simulation Forage May 2025

Analyzed survey results, competitor information, and user behavior, then summarized findings through data visualization and user-centered recommendations.

SKILLS

Data & Programming: Python, SQL, R, Excel, Pandas, NumPy Visualization & Reporting: Power BI, Tableau, Matplotlib, PowerPoint Analytics: Data cleaning, data validation, statistical modeling, regression, time series, anomaly detection, feature engineering, model evaluation Databases: MySQL, PostgreSQL, MongoDB

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