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Amith Thomas

Amith Thomas

Business Analyst | University of Southampton
Portswood, Southampton

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About Amith Thomas:

As a recent graduate with a strong academic background in Business Analytics, I am seeking to leverage my analytical skills and problem-solving abilities as an entry-level business analyst. Through my studies and various project experiences, I have developed a solid understanding of business concepts, as well as proficiency in data analysis tools and techniques.


I am confident that my academic background, project experience, and data analysis skills make me a strong candidate for an entry-level business analyst role. I possess strong communication and interpersonal skills, with an ability to work well in a team and adapt to new challenges. I am eager to continue developing my skills and contributing to the success of a dynamic organization.

In my free time, I enjoy volunteering with local charities and I am passionate about sustainability and environmental issues. I am also a photographer and enjoy playing football, cooking and travelling. I am open to new opportunities and am looking forward to hearing from you. My references are available upon request.

Experience

  • During my internship at the University of Southampton, I worked on a project involving Electric Vehicle (EV) charging stations, where I collected and reviewed data from 50+ EV owners to statistically analyze and interpret their preferences in choosing charging stations for CRM purposes. I also contributed to the development of a more intelligent EV routing application and collaborated with multi-disciplinary academics in engineering to drive project objectives.
  •  In my project at Insensys Ltd., I conducted requirement gathering sessions with business stakeholders to define project scope and objectives, and document requirements using Agile methodology. I also conducted exploratory data analysis (EDA) and statistical analysis to identify insights and provided recommendations through data-driven decision-making. Additionally, I collaborated with cross-functional teams to implement and optimize business processes and reporting.

 My experience has helped me develop excellent analytical, problem-solving, and communication skills, which I believe will be an asset in this role. I am also highly motivated and results-driven, with a strong ability to think strategically and work well under pressure.

Education

This is a STEM degree program that focuses on the study of business analysis techniques, the development of analytical skills, and the use of data and technology to enhance business performance and solve problems for organizations.

During the program, I gained practical knowledge and an understanding of key concepts and techniques in business analytics, including the utilization of R programming to perform statistical analysis on large datasets. Additionally, I developed strong problem-solving skills by improving my algorithmic thinking and implementing complex algorithms using advanced Python programming through the Computational Methods module.

I also learned how Information Systems and analytical tools such as Microsoft Excel and Power BI can be utilized to tap into data and support decision-making processes through the Data Analytics and Decision Making module. In the Quantitative Research in Finance module, I learned about the financial applications of econometric methods and utilized statistical software like Stata to perform regression analysis, hypothesis testing, and more.

Moreover, the Advanced Analytics module equipped me with knowledge in data management using database engines, Generalized Linear Models (GLMs) with embedded variable selection, big data solutions and technologies, and machine learning. I designed and implemented Algorithmic Trading Strategies using Python.

Other modules covered in the program include Optimization and Decision Modeling, Strategic Analytics, and Simulation. For my dissertation, I developed an Agent-Based Simulation model to determine team performance under different scenarios. The model incorporated over 4 human behaviours into the simulation, simulating 1000+ runs to increase accuracy.

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