Welcome to my Portfolio!

About Me 🙂

Hi, I’m Manal JEWA, a customer success professional with a strong data-driven mindset, leveraging my expertise in data analysis to drive business insights and process optimization.

With hands-on experience in the agricultural e-commerce sector, I have leveraged data to enhance customer satisfaction, optimize user experience, and improve operational efficiency. My role involved analyzing purchasing behaviors, monitoring key performance indicators, and using insights to refine business strategies.

To deepen my technical skills, I completed a Data Analysis certification at DataScientest, accredited by l’École des Mines de Paris, where I gained expertise in SQL, Python, machine learning, and data visualization. My strength lies in bridging the gap between business needs and data insights, ensuring that companies make informed, strategic decisions.

I’m open to opportunities across Data and Customer Success domains — whether as a Business/Data Analyst, Customer Insights Analyst, or in a technical CSM role — where I can leverage both my analytical skills and customer-facing experience to support data-driven decisions and enhance the overall customer journey.

Let’s connect! 🚀.

Key Skills & Technologies 💻

Data Analysis & Visualization: Excel, Power BI, Tableau
Programming Languages: SQL, Python (Pandas, NumPy, Matplotlib, Seaborn, Plotly)
Data Cleaning & Preparation: Data wrangling, handling missing data, data normalization
Business Intelligence: Creating interactive dashboards and reports
Customer Analytics: Customer segmentation, behavior analysis, KPIs
Machine Learning: Basic knowledge of Scikit-learn for predictive modeling
Streamlit: Building interactive web apps for data visualization and deployment

Data Projects 📊

Here are some of the projects I’ve worked on that demonstrate my expertise in data analysis. These projects focus on data cleaning, analysis, and visualization, with an emphasis on delivering actionable insights.

1. Marketing Campaign Success Prediction - (Data Scientest) - February 2025

Objective: Develop a predictive model to anticipate whether a customer will respond positively to a marketing campaign.

Actions:

Performed exploratory data analysis (EDA) on a dataset with 11,162 rows and 17 variables.
Preprocessed the data (handling missing values, encoding categorical variables, and normalizing features).
Modeled using multiple algorithms: Logistic Regression, Random Forest, and Gradient Boosting.
Best model: Random Forest with an F1-score of 85%.

Technologies Used: Python, Scikit-Learn, Matplotlib, Seaborn, Plotly

🔗 Link to the project on GitHub

🔗 Link to the project on Streamlit

2. Call Center Performance Analysis with Power BI - (Data Scientest)- January 2025

Objective: In this project, I analyzed the performance of a call center using Power BI. I focused on key areas such as customer service performance, revenue trends, and employee efficiency.

Actions:

Data cleaning and transformation using Power Query.
Star schema modeling for efficient analysis.
Interactive Power BI dashboard with KPIs to evaluate service levels, revenue, and employee performance.

Technologies Used: Power BI, Power Query, Dax.

🔗 Link to the project on GitHub

3. Customer Reviews Analysis - (Data Scientest)- December 2024

Objective: This project aims to predict customer ratings for e-commerce orders and analyze key factors influencing customer satisfaction. By understanding these factors, businesses can enhance the user experience and drive sales growth.

Actions:

Extracted and processed relational data using SQL.
Conducted exploratory data analysis and visualized key trends.
Engineered new features, including delivery duration and historical review metrics.
Applied Random Forest for classification, merging rating categories to manage class imbalance.
Evaluated model performance and analyzed misclassification patterns.

Technologies Used: Python, SQL, Scikit-Learn, Matplotlib, Seaborn

🔗 Link to the project on GitHub

4. Sales Trends and Customer Behavior Analysis – (Personal Project) - December 2024

Objective: Analyze sales performance for an e-commerce company using SQL to extract key insights about orders, customers, and products.

Actions:

Analyzed over 500,000 transactions from the Online Retail dataset.
Identified top-selling products, periods of high demand, and segmented customers based on their revenue.
Calculated product return rate (9%) and recommended actions to reduce anomalies.
Automated key performance indicators (KPIs) using SQL and visualized the results in Power BI.

Technologies Used: SQL, Power BI

🔗 Link to the project on GitHub

What’s Next in My Learning Journey? 🚀

I am dedicated to continuously expanding my data analytics expertise, with a strong focus on the following areas:

SQL Mastery: Enhancing my skills in advanced SQL techniques, including query optimization, complex joins, and window functions for efficient data analysis.
Advanced Data Visualization: Developing expertise in Tableau and Power BI to create dynamic, interactive dashboards that drive decision-making.
Machine Learning Applications: Applying predictive modeling and classification techniques to real-world datasets to extract deeper insights.
Data Storytelling: Refining my ability to communicate data-driven insights clearly and effectively, ensuring stakeholders can take meaningful action.

Why I’m a Great Fit for Your Team 🤝

Customer-Driven Data Expertise: With a strong foundation in customer insights and business intelligence, I leverage data to enhance user experience, optimize strategies, and drive growth.
Proven Analytical Skills: My experience, combined with advanced training at DataScientest, has equipped me with expertise in SQL, Python, and data visualization, allowing me to transform complex datasets into actionable insights.
Strategic and Impact-Driven: Passionate about data, I thrive in digital marketing, e-commerce, finance, and other data-driven industries, where I can help businesses make informed decisions and gain a competitive edge.

Contact Me 📩

I would love to discuss how I can contribute to your organization’s data needs. Feel free to reach out to me through the following:

📧 Email: manal.jewa@gmail.com

🔗 LinkedIn: My LinkedIn Profile

🔗 GitHub: My GitHub Profile

Thank You!

Thank you for visiting my portfolio! I’m seeking opportunities in data analytics or customer success with a data-driven approach. Always eager to learn and tackle new challenges, I’d love to connect for potential opportunities, collaborations, or insightful discussions!