I’m Teslim Uthman, a finance and data analytics professional with over a decade of expertise in financial reporting, data analysis, and accounting. Throughout my career, I’ve built a strong foundation in financial systems and data-driven decision-making, leveraging tools like SQL, Python, R Language, Advance Excel, and Power BI to extract, process, and analyze financial data efficiently. My experience spans various industries, where I’ve consistently enhanced operational efficiency, optimized financial reporting, and delivered actionable insights to drive strategic business decisions.
My GitHub repository showcases some of the key projects and tools I’ve worked on, especially in the fields of financial modeling, variance analysis, and data analytics. You’ll find examples of how I’ve used SQL to automate data extraction, streamline reporting processes, and build predictive models that improve forecasting accuracy. As a firm believer in continuous learning, I’m currently expanding my expertise in machine learning and advanced data science techniques to tackle even more complex financial challenges.
Feel free to explore my projects, and let’s connect if you’re interested in collaborating on data-driven financial solutions!
Overview:
As a data-driven finance professional, I leverage SQL to efficiently manage, analyze, and transform large datasets. Whether it's building complex queries or optimizing database performance, SQL is a key tool in my analytics toolkit.
Skills & Proficiencies:
- Query Optimization: Writing efficient and performant queries to retrieve large amounts of financial data.
- Data Extraction & Transformation: Expertise in using SQL for data cleaning and transforming raw data into actionable insights.
- Database Design & Management: Proficient in creating relational databases, including normalization and indexing to ensure data integrity.
- Advanced SQL Functions: Using joins, subqueries, and window functions to perform advanced data analysis.
- Stored Procedures & Triggers: Automating repetitive tasks and ensuring data accuracy with SQL stored procedures and triggers.
Applications in Finance & Data Science:
- Variance Analysis: Using SQL to extract and analyze financial variances between actuals and forecasts.
- Treasury & Liquidity Analysis: Querying complex data sets to generate reports on cash flows, liquidity, and financial risk.
- Data-Driven Decision Making: Supporting business decisions by generating insights from SQL databases.
- SQL for Machine Learning: Preparing financial data in SQL for integration with machine learning algorithms.
Notable Projects:
- My SQL Journey: From Fundamentals to Advanced Data Mastery: Reflecting on my SQL journey from basic to advanced.
- Financial Data Modeling: Built a dynamic SQL database model to analyze financial performance across multiple business units.
- Cash Flow Optimization: Developed queries to track and optimize liquidity, improving cash flow management.
- Data Integrity Validation: Created SQL scripts for verifying and cleaning financial data before integration into analytics pipelines.
Tools & Technologies:
- PostgreSQL
- MySQL
- SQLite
Overview:
Pandas is my go-to tool for data manipulation and analysis. I use it to handle everything from large datasets to financial time series data with ease and efficiency.
Skills & Proficiencies:
- Data Wrangling: Cleaning and transforming financial data for analysis.
- Time Series Analysis: Using Pandas for working with time-indexed data for forecasting and trend analysis.
- Merging and Joining: Combining multiple data sources for comprehensive analysis.
- GroupBy Operations: Aggregating data to perform complex analyses.
Notable Projects:
- Financial Time Series Analysis: Analyzed stock market data to identify trends and make predictions.
- Data Cleaning and Transformation: Cleaned and transformed large financial datasets to prepare them for machine learning models.
Overview:
I use machine learning to build models that can predict and classify financial outcomes, leveraging tools like Python, Scikit-Learn, and TensorFlow.
Skills & Proficiencies:
- Regression and Classification Models: Predicting financial outcomes based on historical data.
- Model Evaluation: Using metrics like accuracy, precision, and recall to evaluate model performance.
- Feature Engineering: Creating new features to improve model performance.
- Hyperparameter Tuning: Optimizing models using techniques like grid search.
Notable Projects:
- My Machine Learning Journey in Financial Data Analysis: A comprehensive exploration of ML techniques.
- Stock Price Prediction: Built a regression model to predict future stock prices based on historical data.
- Credit Risk Classification: Developed a classification model to assess the risk of loan default.
Overview:
Python is at the core of all my data science projects. From scripting to full-scale machine learning models, Python is the key to unlocking insights from data.
Skills & Proficiencies:
- Data Manipulation: Using Pandas, NumPy, and other libraries to manipulate large datasets.
- Automation: Writing Python scripts to automate repetitive tasks.
- Data Visualization: Using libraries like Matplotlib and Seaborn to create insightful visualizations.
Notable Projects:
- Python for Finance: Built a financial model to forecast future revenue using Python.
- Data Automation Scripts: Developed scripts to automate the extraction and analysis of financial data.
Overview:
R is a powerful tool for statistical analysis, and I use it to conduct in-depth financial analyses, including hypothesis testing and linear regression.
Skills & Proficiencies:
- Data Visualization: Creating advanced plots and graphs with ggplot2.
- Statistical Analysis: Performing t-tests, ANOVA, and regression analyses.
- Data Manipulation: Using dplyr and tidyr for data wrangling and analysis.
Notable Projects:
- Financial Statistical Analysis: Used R to analyze and visualize stock market trends and volatility.
- Predictive Analytics: Built predictive models using R to forecast financial performance.
Overview:
Power BI enables me to create interactive dashboards and reports that turn complex financial data into easy-to-understand visuals.
Skills & Proficiencies:
- Data Modeling: Creating relationships between different data sources for comprehensive analysis.
- DAX Functions: Writing advanced DAX formulas to perform complex calculations.
- Interactive Dashboards: Building visually engaging and interactive financial dashboards.
- Data Visualization: Presenting data insights through powerful visualizations.
Notable Projects:
- Finance Dashboard: Created a Power BI dashboard to monitor key financial KPIs.
- Sales Performance Report: Developed a report to analyze sales performance and identify growth opportunities.
I’m always excited to collaborate on data-driven projects, particularly those involving SQL analytics. Feel free to connect with me!