Data Analyst & Data Scientist
Junior Data Scientist with 2 years of experience using Python, R, SQL, and Machine Learning to solve complex business problems. Passionate about transforming data into actionable insights and developing data-driven solutions that support key business objectives.
About Me
I’m a results-driven Junior Data Scientist with 2 years of experience applying Python, R, SQL, and machine learning analytics to solve real-world business problems and drive data-informed decisions.
My expertise spans data visualization, statistical analysis, machine learning, SQL, Python, Power BI, and Tableau. I’m skilled at identifying business opportunities through exploratory data analysis and translating complex datasets into clear, actionable insights.
I have successfully delivered multiple analytics and machine learning projects, from customer segmentation and behavior analysis to operational efficiency improvements. My work focuses on translating business problems into data-driven solutions with measurable impact.
My Projects & Analysis
Data-driven solutions showcasing my expertise in analytics, reporting, and business intelligence
Walmart Basket Analysis
This project analyzes Walmart sales data in Excel to identify the most frequently purchased product pairs and triplets, supported by Pivot Tables for exploratory analysis. It also determines the top-selling product combinations by day of the week and time of day, revealing valuable customer purchasing patterns.
Predicting House Prices — Data Mining & AI
Developed a complete data mining workflow in KNIME Analytics Platform to predict residential house prices using the Ames, Iowa dataset. Implemented and compared Multiple Linear Regression and Random Forest regression models, incorporating data preprocessing, 10-fold cross-validation and performance evaluation using R², MAE and RMSE. Random Forest achieved R²=0.884 on the test set, outperforming Linear Regression (R²=0.820) across all metrics.
Big Data Analytics — ICLR & OpenAlex
Built a scalable big data analytics solution using PySpark DataFrames in Databricks to analyze ICLR conference submissions and OpenAlex research data. Performed data cleaning, transformation, aggregation, and cross-dataset joins to investigate acceptance rates, reviewer scores, emerging research topics, and citation impact. Identified rapidly growing research trends such as LLMs and analyzed the relationship between peer-review evaluations, reviewer disagreement, and long-term academic influence.
ASOS Business & Financial Analysis
Conducted a comprehensive analysis of ASOS plc, evaluating its financial performance, profitability, liquidity, gearing, and competitive position over a five-year period. Performed competitor benchmarking against Boohoo and Shein, alongside PESTLE, SWOT, and social media analysis to assess key market trends, strategic challenges, and external risks. The analysis identified declining profitability, increasing financial risk, intense competitive pressure, and potential areas for operational improvement, concluding with an investment risk assessment and strategic recommendations.
Lyrical Evolution & Chart Performance — Data Visualisation
Analysed Billboard Hot-100 songs from 2000–2023 using R to investigate how lyrical sentiment, themes, and complexity evolved over time and whether these patterns were associated with chart performance. Cleaned and tokenised lyric data, applied the Bing sentiment lexicon, calculated yearly sentiment and word-count trends, classified lyrics into thematic categories, and analysed the relationship between chart ranking and lyrical sentiment. Developed a composite visualisation using ggplot2, incorporating trend lines, bar charts, and scatter plots, while evaluating visualisation accessibility, colour-vision considerations, and potential sources of misleading interpretation.
Education & Certifications
MSc in Data Science
University of Sheffield • 2025-2026
BSc in Translation Studies
Azerbaijan University of Languages • 2016-2020
Certificate in Data Analytics
Handex • 2024
MOSE Excel Expert
Microsoft • 2024
Get In Touch
I'm always interested in hearing about new projects and opportunities. Feel free to reach out!