Hi my name is Martins Umunna, Welcome to my Portfolio!.
I am A Data Scientist| Data Analyst passionatly adept at drawing insights from data and help Businesses make data-driven strategic decisons.
With 4 years of experience in the Luxury Business, I possess a deep understanding of statistical analysis, machine learning algorithms, and data visualization techniques using Tableau and Power BI.
My expertise lies in utilizing advanced statistical models and machine learning algorithms to uncover patterns, trends, and correlations within data.
I am skilled in programming languages such as Python, R, and SQL, and have experience in data manipulation,Analytics, cleaning, and preprocessing.
In this project, I conducted an in-depth analysis of medical insurance charges to understand the factors that contribute to the variation in healthcare costs. By analyzing a dataset of insurance charges, I aimed to uncover patterns and insights that can help stakeholders in the healthcare industry make informed decisions.
Using statistical modeling techniques and data visualization, I examined the relationships between various factors such as age, BMI, region, and smoking status with insurance charges. Through exploratory data analysis, I discovered intriguing patterns and trends that shed light on the key drivers of medical costs.
Furthermore, I employed machine learning algorithms, such as linear regression, to develop predictive models for estimating future insurance charges based on patient attributes. These models provide valuable insights into the potential cost implications for different individuals, helping both insurance providers and individuals make informed decisions regarding their healthcare coverage.
By presenting the findings and implications of this analysis, I aim to contribute to the ongoing discussions on healthcare cost management and encourage data-driven decision-making in the industry.
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In this project, I conducted an A/B testing analysis to optimize the shipping modes for a superstore company, specifically comparing the performance of Standard Class and First Class. By carefully designing and executing the experiment, I aimed to uncover insights that can enhance the company's logistics operations and customer experience.
The findings from this A/B testing project provide valuable insights into the strengths and weaknesses of Standard Class and First Class shipping modes. This information can guide the company's decision-making process, allowing for data-driven adjustments to optimize the shipping strategy.
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In this Project, I Generated a Sales dummy dataset, preprocessed and transformed the data and used it to understand how Elysian Fragrances have performed over the past 5years..
In this Project, I used Various Data Cleaning Techniques to preprocess and transform data of Nashville Housing for further Analysis.
In this Project, I conducted Exploratory Dat Analysis on Covid-19 Data to understand, Metrics such as Deaths, Infections, Vaccinations and Population Percentages.
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Here, You can find all my Data Visualizations that explains the summry of my analysis and projects..