A reliable and experienced Data Scientist, Artificial Intelligence Business Leader with over 6 years of experience executing data-driven solutions to increase efficiency, accuracy, to complex business problems.
Worked on captivating data science projects and Audit assurance engagements with extensive experience in domains like; Hospitality, Banking, HR Analytics, Retail, Finance, Tea Industry, Risk Management, Information Systems and Others.
I am thoroughly enjoying getting back to coding with a focus on data, databases, and analysis. Now I’d like to derive actionable insights and provide solutions to business problems with my data analytics and data science skills. My work involves Fraud Detection, Finance and Risk Analytics, Forecasting Models, applying statistical methods in a business context to help the organization address key business questions and take evidence-based decisions. This includes hypothesis testing which form the basis for evidence-based business decisions, Interpret the results of statistical analyses and making inferences about the population using the sample data. Apply linear regression on data and identify factors that will help drive business decisions for clients and others. I am able to asses’ data and help organizations wanting to leverage on the power of AI (Artificial Intelligence) to make informed strategic business decisions.
I have progressively transitioned from an Accountant >> Business Inteligence Analyst >> Data Scientist->.With every transition in the role, I have enriched myself and contributed significantly to the growth of all stakeholders involved. I intend to continue doing hands-on data engineering and data analysis while developing additional technical and leadership skills.
📍Programming: Python,SQL,KNIME
📍Visualization: Tableau,Power BI,Advanced Excel
📍Data Scrapping, Data Mining and APIs
📍Statistics: Descriptive Statistics, Inferential Statistics, Hypothesis Testing, Regression Analysis,AB Testing.
📍Data wrangling and database management : MySQL,MongoDB,Oracle
📍Machine learning and deep learning: Regression Modeling, Decision Tree, Random Forest, AdaBoost, GradientBoosting XGBoost, K-means Clustering, Feature Extraction.
📍Cloud computing: Amazon Web Service (AWS),Microsoft Azure,Google Cloud
📍Hospitality, Banking, HR Analytics, Retail, Finance,Tea Industry, Online Risk Management.
*Code*: https://github.com/Mugangasia/car-prediction-model/blob/master/car-price-prediction-linear-regression-rfe.ipynb
*Project Brief*
A Chinese automobile company Geely Auto aspires to enter the US market by setting up their manufacturing unit there and producing cars locally to give competition to their US and European counterparts.
They have contracted an automobile consulting company to understand the factors on which the pricing of cars depends. Specifically, they want to understand the factors affecting the pricing of cars in the American market, since those may be very different from the Chinese market. The company wants to know:
- Which variables are significant in predicting the price of a car
- How well those variables describe the price of a car
Based on various market surveys, the consulting firm has gathered a large dataset of different types of cars across the Americal market.
*Business Goal*
You are required to model the price of cars with the available independent variables. It will be used by the management to understand how exactly the prices vary with the independent variables. They can accordingly manipulate the design of the cars, the business strategy etc. to meet certain price levels. Further, the model will be a good way for management to understand the pricing dynamics of a new market.
📍Loan Default Prediction Model
📍House Price Prediction Model
📍Diamond Price Predictor
📍MIcrosoft Movie Studio (EDA)
📍Hypothesis Testing (Wine Quality)
📍Tableau Projects https://public.tableau.com/app/search/vizzes/Bravin%20Mugangasia
- Data Science Manager - Triangle Healthcare Consulting Inc