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Schedule Interview NowMy name is Raha K. and I have over 2 years of experience in the tech industry. I specialize in the following technologies: Python, R, Stata, Statistics, Microsoft Excel, etc.. I hold a degree in Bachelor's degree, Master of Philosophy (MPhil). Some of the notable projects I’ve worked on include: Trends in UK Smartphone Usage 2022–2024, Energy Storage System Performance and Cost Optimization Analysis, Influence of Demographic Factors on Gang Involvement Patterns, Comprehensive Analysis of Bank Profitability in 2024, Analyzing the Covid-19 She-cession and EU Gender Labor Inequalities, etc.. I am based in Madrid, Spain. I've successfully completed 6 projects while developing at Softaims.
I employ a methodical and structured approach to solution development, prioritizing deep domain understanding before execution. I excel at systems analysis, creating precise technical specifications, and ensuring that the final solution perfectly maps to the complex business logic it is meant to serve.
My tenure at Softaims has reinforced the importance of careful planning and risk mitigation. I am skilled at breaking down massive, ambiguous problems into manageable, iterative development tasks, ensuring consistent progress and predictable delivery schedules.
I strive for clarity and simplicity in both my technical outputs and my communication. I believe that the most powerful solutions are often the simplest ones, and I am committed to finding those elegant answers for our clients.
Main technologies
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Potentially possible
IBM Spain
Analyzed nationwide UK smartphone usage data from 2022 to 2024, focusing on changing trends and demographic segmentation (age groups, socio-economic status, and regions). Cleaned and transformed raw survey data in Excel, then conducted advanced statistical and correlation analyses in Python (Jupyter Notebook). Identified top and emerging activities—particularly in video-based functions—and delivered actionable insights for service providers, app developers, and marketers seeking to optimize user engagement.
Conducted a comprehensive analysis of an Energy Storage System (ESS) to evaluate energy efficiency, system health, and performance. Utilized statistical methods including descriptive statistics, seasonal decomposition (7-day cycle), and anomaly detection to identify operational inefficiencies. Analyzed areas such as battery usage to develop actionable insights. Provided recommendations for load management, battery optimization, inverter performance, and cost reduction strategies. The analysis enhanced system reliability, reduced energy costs, and improved overall operational efficiency.
In this study, I investigated how demographic factors influence gang involvement . I conducted comprehensive data preprocessing, and outlier removal for data integrity. Utilizing statistical methods such as chi-square tests, logistic regression, and Ordinary Least Squares (OLS) regression, I analyzed the relationships between variables like age, marital status, parental status, and race with gang membership and the age of joining gangs. The analysis revealed significant insights into how familial connections, social influences, and demographic characteristics contribute to gang participation.
In this project, I analyzed the profitability of listed banks in 2024 by examining key metrics such as Parent Net Profit, Return on Equity (ROE), and Return on Total Assets (ROA). The study identified drivers of high profitability, including scale of operations, operating revenue, interest income dominance, efficient cost management, and effective tax contributions. Through data correlation and strategic financial management, the analysis provided insights into how large-scale operations and operational efficiency contribute to superior performance in the banking sector.
Conducted a comprehensive analyzing the Covid-19 she-cession in the EU labor market. The project examined how the pandemic exacerbated existing gender disparities, focusing on both intra-household and extra-household feminization trends. By analyzing statistical data from Eurostat and other sources, I identified the sectors most affected, compared the impact with previous recessions, and assessed future implications for women's labor market participation. The findings highlight the need for equitable labor force reforms to achieve a gender-balanced economic recovery.
Bachelor's degree in Mathematics
Master of Philosophy (MPhil) in Economic Analysis
2021-01-01-2023-01-01