I’m Elham Shamsi Nejad, a Data Analyst and AI Developer with a Ph.D. in Computer Engineering and experience in data science, machine learning, Python, SQL, and business intelligence. I help businesses turn raw Excel and CSV data into clear, actionable insights. My experience includes data cleaning, exploratory data analysis, KPI reporting, sales analysis, product performance analysis, customer segmentation, trend analysis, statistical analysis, data visualization, and interactive dashboards. I build practical data solutions using Python, Pandas, Matplotlib, and Streamlit. I also have experience in machine learning, anomaly detection, fraud detection, big data analytics, and scalable data processing. I focus on delivering accurate, practical, and easy-to-understand analysis that helps businesses make better decisions.…

Elham Shamsi Nejad

I’m Elham Shamsi Nejad, a Data Analyst and AI Developer with a Ph.D. in Computer Engineering and experience in data science, machine learning, Python, SQL, and business intelligence. I help businesses turn raw Excel and CSV data into clear, actionable insights. My experience includes data cleaning, exploratory data analysis, KPI reporting, sales analysis, product performance analysis, customer segmentation, trend analysis, statistical analysis, data visualization, and interactive dashboards. I build practical data solutions using Python, Pandas, Matplotlib, and Streamlit. I also have experience in machine learning, anomaly detection, fraud detection, big data analytics, and scalable data processing. I focus on delivering accurate, practical, and easy-to-understand analysis that helps businesses make better decisions.…

Available to hire

I’m Elham Shamsi Nejad, a Data Analyst and AI Developer with a Ph.D. in Computer Engineering and experience in data science, machine learning, Python, SQL, and business intelligence.

I help businesses turn raw Excel and CSV data into clear, actionable insights. My experience includes data cleaning, exploratory data analysis, KPI reporting, sales analysis, product performance analysis, customer segmentation, trend analysis, statistical analysis, data visualization, and interactive dashboards.

I build practical data solutions using Python, Pandas, Matplotlib, and Streamlit. I also have experience in machine learning, anomaly detection, fraud detection, big data analytics, and scalable data processing.

I focus on delivering accurate, practical, and easy-to-understand analysis that helps businesses make better decisions.

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Skills

Experience Level

Data Science
Expert
Python
Expert
SQL
Expert
Data Visualization
Expert
Docker
Intermediate
Spark
Intermediate
TensorFlow
Intermediate
Hadoop
Intermediate
Keras
Intermediate
Prompt Engineering
Intermediate
PyTorch
Intermediate
ETL
Intermediate
Kubernetes
Beginner
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Language

English
Intermediate
English
Advanced

Work Experience

Independent Researcher | Specialist in Data Science, Big Data, and Cloud Computing
January 1, 2021 - Present
Published high-impact research (2021–2025) on big data anonymization and real-time data processing, with a focus on in-memory and stream processing models for scalable privacy preservation. Contributed to interdisciplinary privacy and security research for data-driven financial systems, including fraud detection and large-scale analytics.

Education

Ph.D. in Computer Engineering (Software) at Islamic Azad University, Central Tehran Branch
January 1, 2016 - January 1, 2025
M.Sc. in Computer Engineering (Software) at Islamic Azad University, Science and Research Branch, Rasht
January 1, 2011 - January 1, 2013
B.Sc. in Computer Engineering (Software) at Islamic Azad University, Lahijan Branch
January 1, 2007 - January 1, 2011

Qualifications

Generative Artificial Intelligence Certification
January 1, 2023 - September 15, 2026
Zero to Hero Data Science Project with GPT Certification
January 1, 2023 - September 15, 2026
Data Scientist Training Course
January 1, 2020 - September 15, 2026
International Blockchain and Cryptocurrency Certification
January 1, 2019 - September 15, 2026
English Proficiency Test (EPT)
January 1, 2018 - September 15, 2026
Teacher Training Course (40 hours)
January 1, 2013 - September 15, 2026

Industry Experience

Education, Computers & Electronics, Financial Services, Professional Services, Software & Internet
    Business Sales Dashboard & KPI Analysis
    Business Sales Dashboard & KPI Analysis This project focuses on analyzing business sales performance through key performance indicators (KPIs), product performance, category performance, and sales trends. The goal is to turn raw transaction data into a clear view of overall business performance. Key KPIs Total Revenue Total Orders Total Customers Units Sold Average Order Value (AOV) Units per Order Sales Analysis Monthly revenue analysis Sales growth and decline Product performance Category performance Best-performing products Best-performing sales periods Technologies Python, Pandas, Data Analysis, Data Visualization Business Value The dashboard provides a concise overview of sales performance and helps businesses identify important changes in revenue, product demand, and category performance. It demonstrates my ability to analyze business data, calculate meaningful KPIs, identify sales trends, and present analytical results in a format that is easy to understand.…
    Customer Segmentation & Sales Analysis with Python

    Customer Segmentation & Sales Analysis with Python

    This project uses Python and data analysis techniques to understand customer purchasing behavior and segment customers based on their sales activity.

    The analysis identifies different customer groups and helps businesses understand which customers generate the most value and which customers may require re-engagement.

    Key Analysis

    • Customer purchase frequency
    • Total customer spending
    • Number of orders per customer
    • Customer segmentation
    • Identification of VIP customers
    • Identification of regular customers
    • Identification of new customers
    • Identification of inactive or lost customers
    • Analysis of high-value customers
    • Identification of customers who may need re-engagement

    Customer Segments

    The analysis categorizes customers into four practical groups:

    • VIP – high-value customers with strong purchasing activity
    • Regular – customers with consistent purchasing behavior
    • New – recently acquired customers
    • Lost – customers who have become inactive

    Technologies

    Python, Pandas, Data Analysis, Data Visualization

    Business Value

    Customer segmentation allows businesses to move beyond overall sales numbers and understand who their customers are.

    The results can help businesses identify valuable customers, recognize inactive customers, improve customer retention strategies, and focus marketing efforts on specific customer groups.

    This project demonstrates my ability to transform raw transaction data into customer-level insights that can support business decision-making.

    QuickSales AI – Sales Intelligence Dashboard
    QuickSales AI – Sales Intelligence Dashboard QuickSales AI is a Python-based sales analytics and business intelligence tool designed to transform raw sales data from CSV or Excel files into clear, actionable business insights. The dashboard analyzes sales performance, products, categories, customers, and sales trends to help businesses understand what is driving their revenue and where attention is needed. Key Features Sales KPIs including Total Revenue, Orders, Customers, Units Sold, and Average Order Value Product performance analysis Category-level sales analysis Monthly sales trends and growth Customer segmentation into VIP, Regular, New, and Lost customers Identification of high-value and inactive customers Business-focused insights and recommendations Interactive dashboard built with Python and Streamlit Support for CSV and Excel sales data Technologies Python, Pandas, Streamlit, Matplotlib, Data Analysis, Data Visualization Business Value Instead of manually analyzing a large sales spreadsheet, a business can use this tool to quickly identify its strongest products, valuable customers, sales trends, and areas requiring attention. The project demonstrates my ability to turn raw business data into structured analysis, visual reports, and practical insights.…