parinazmdi / lab-dw-data-cleaning-and-formatting

Hi, I'm Parinaz!

About Me

I am deeply invested in sustainability and data-driven innovation, with a strong financial background in risk management. My career is a testament to a lifelong dedication to learning and applying analytical skills to decipher complex financial data. My expertise lies in harnessing statistical and machine learning methods to unearth insights across various business landscapes, particularly where they intersect with sustainable development. I'm eager to engage with roles that challenge my analytical acumen and align with my dedication to data-centric, eco-conscious growth.

Current Work

• 🔭 I’m currently enhancing my skills in data visualization(PL-300 certificate), exploring how to effectively communicate insights through visual tools and dashboards.
• 💬 I speak English
• 📌 Currently, I am seeking opportunities in data analysis and visualization that allow me to apply my skills in machine learning, statistical analysis, and integrate them with my background.

Skills and Knowledge

• Data Analysis & Visualization: Proficient in using tools like Excel, Tableau to analyze data and create compelling visualizations.
• Programming Languages: Skilled in Python for statistical analysis and machine learning.
• Machine Learning: Familiar with supervised and unsupervised learning algorithms, and libraries like Scikit-Learn and TensorFlow.
• Statistical Analysis: Strong grasp of statistical concepts.
• Financial Acumen: Solid understanding of financial principles, particularly risk management, and their application in data analysis.
• Database Management: Proficient in SQL for database querying, data manipulation, and management.
• Sustainability and Innovation: Knowledgeable about sustainable practices and how to leverage data for eco-friendly business solutions.
• Problem-Solving: Ability to tackle complex problems by applying data-driven decision-making processes.
• Continuous Learning: Committed to ongoing professional development, currently working towards an IBM Professional Data Analyst Certificate.
• Collaboration and Communication: Effective at working within diverse teams and communicating technical concepts to non-technical stakeholders.

Projects

Credit Risk Assessment

• Description: Developed a predictive model to assess borrower creditworthiness and potential loan defaults, leveraging financial data and risk management principles.
• Skills Applied: Financial acumen in risk management, advanced statistical analysis, machine learning with Python, data visualization for reporting insights.

Book Recommender System

• Description: This Recommender System is an interactive tool that provides personalized book suggestions based on user queries, utilizing web scraping, API integration, and unsupervised machine learning.
• Skills Applied: Python programming, data handling, machine learning, API integration, web scraping, user interface design.

Donation Prediction and Amount Forecasting

• Description: Built a dual-purpose model to forecast potential donations and classify likely donors, aiding in effective fundraising strategies for non-profits.
• Skills Applied: Statistical analysis for prediction accuracy, machine learning for classification and regression tasks, SQL for data querying, and Python for model development.

In all these projects, the quality of data plays a crucial role. Accurate and clean data is essential for developing effective models and obtaining reliable predictions.