Data Analyst

FATIMA SHAMILOVA

WASHINGTON, D.C., US • *************@*****.*** Tel.: +1-202-***-****

LinkedIn: https://www.linkedin.com/in/fatimashamilova/ GitHub: https://github.com/Fatimashamilova Data Analyst with 3 years proven experience in analytics, automation, and business process optimization across industries including operations, e-commerce, and B2B strategy. Skilled in Python, SQL, Power BI, and Tableau, with hands-on expertise in data modeling, ETL automation, and performance analytics. Adept at transforming raw data into actionable insights that drive profitability, operational efficiency, and strategic decision-making. Holds a Master’s in Data Modeling, Warehousing, and Database Administration (GPA 4.0) and a track record of building scalable, data-driven solutions that enhance business performance. EDUCATION

Bay Atlantic University M.Sc. Data Modeling, Warehousing, and Database Administration Jan 2023 – May 2025 Washington, D.C. GPA: 4.0

Kyrgyz National University B.Sc. Economics and Management Sep 2016 – June 2020 Bishkek, Kyrgyz Republic GPA: 3.8

EXPERIENCE

Dream Aero Boeing 737 NG flight simulator – Data Analyst (Operations & Sales) Jan 2024 – now Bethesda, Maryland

§ Partner cross-functionally with executive leadership and operations teams to conduct advanced performance diagnostics and develop data- driven strategies improving profitability and resource allocation.

§ Architect and manage interactive Power BI and Tableau dashboards integrating multi-source data (sales, CRM, and operational KPIs) to deliver real-time insights across 10K + monthly transactions.

§ Apply SQL-based data modeling and Python-driven statistical analysis to identify trends in customer acquisition, retention, and utilization, enabling a 15 % improvement in asset utilization and 12 % growth in recurring revenue.

§ Lead the standardization and automation of enterprise reporting through ETL optimization and version-controlled SQL pipelines, cutting manual reporting time by 40 % and enhancing data reliability. Liquisto Technologies – Data Analyst Jan 2023 – Dec 2023 Remote

§ Applied Python- and SQL-based data quality frameworks to perform deduplication, anomaly detection, and consistency validation on 5K+ product and customer records, achieving a 98% increase in database accuracy and reliability for business reporting.

§ Conducted predictive and diagnostic analysis to evaluate demand patterns, procurement cycles, and excess inventory risk — driving a 15% improvement in inventory turnover efficiency and enhanced working-capital visibility. Amazon – Business Analyst (Internship) Sep 2022 – Dec 2022 Remote

§ Supported the sales analytics team in evaluating regional and category-level performance using SQL, Python, and Excel-based models.

§ Built and optimized automated reports and dashboards tracking daily sales KPIs, conversion rates, and product trends, improving reporting turnaround by 60%.

TECHNICAL SKILLS

Programming:

DS/ML Libraries

Visualization:

ML Algorithms:

Databases:

Analytics/BI Tools:

ETL / Cloud:

Python, SQL, R, HTML, JSON

Pandas, NumPy, scikit-learn, XGBoost, PyTorch (basics), regex Matplotlib, Seaborn, ggplot2

Naïve Bayes, K-Nearest Neighbors (KNN), Logistic & Linear Regression, Decision Trees, Random Forest MySQL, MS SQL Server, MongoDB

Jupyter Notebook, Google Colab, Tableau, Power BI

AWS (Glue, Redshift, Airflow), Pentaho, GCP, REDCap ACADEMIC PROJECTS

Retail Product Data Analysis (Myntra Catalog) [GitHub] Python, Pandas, NumPy, Matplotlib, Seaborn, Jupyter Notebook

§ Conducted data cleaning and wrangling on a retail product catalog dataset (10,000+ entries).

§ Performed exploratory data analysis (EDA) to uncover insights on product categories, pricing trends, and brand performance.

§ Built visualizations (price distributions, category/brand comparisons, rating analysis) to support data-driven retail decision-making. Movie Reviews Sentiment Analysis

§ Processed and analyzed 10,000+ movie reviews using Python (scikit-learn, NLTK, Pandas) to classify sentiment polarity.

§ Implemented Bag-of-Words (BoW) and TF-IDF vectorization techniques and trained Naïve Bayes and K-Nearest Neighbors (KNN) models, achieving 89% classification accuracy.

§ Conducted exploratory text analysis, tokenization, and data visualization to identify the most frequent positive and negative sentiment terms.

Data Engineer Salary Analysis

§ Conducted an in-depth salary trend analysis on 2,000+ global data engineering records (2020–2024) using Python, Pandas, NumPy, and Seaborn.

§ Cleaned and encoded 10+ categorical features, performed exploratory data analysis (EDA), and visualized salary variations across 4 experience levels, 3 company sizes, and multiple employment types, uncovering ~28% higher compensation for senior-level engineers and clear upward trends in U.S. and European markets.

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