Mitch Rahman | Data Science Student

Mitch Rahman

Data Science Student

Based in London, UK

About

Turning numbers into stories that captivate and persuade that's what lights my fire! With every dataset, I like to delve deep to uncover hidden insights that empower impactful decisions. Through hands-on experiences, I've honed my ability to pick apart datasets, extract meaningful patterns, and craft insightful narratives that drive business value. I can use fancy tools like SQL, Python, Power BI, and Tableau to break down complex findings into simple yet impactful stories that inform and inspire. However, my secret weapon is my collaboration skills, simply because the best insights come from shared minds.

Skills

Projects

London Employment Analysis (2000–2024)

Analysed employment trends across London's 33 boroughs using Python and pandas. Cleaned and transformed the dataset, performed exploratory data analysis (EDA), engineered new features and created visualisations to identify long-term employment trends and the impact of COVID-19.

Sales Insights

At Atil Q Hardware, the Sales Director faces challenges in tracking and understanding sales performance due to unreliable information from regional managers. The project aims to develop a concise sales insight dashboard highlighting revenue, sales quantity, and profit margin for each region.

Bank Loan

A complete Bank Loan Report is required in order to monitor and analyse our bank's lending activity and performance. The purpose of this report is to give insight into important loan-related variables and how they evolve over time.

Ecommerce Sales

Develop a comprehensive dashboard for a US-based ecommerce company, presenting key Year-to-Date (YTD) metrics including sales, profit, quantity sold, and profit margin. The dashboard should feature Year-over-Year (YoY) growth analysis with YTD sparklines for monthly trends.

Experience

2023 - 2023

Data Analyst Intern At IO-Sphere

• Created a business case for a loyalty program, conducting competitive analysis; projected a 25% increase in customer retention. • Led and executed customer segmentation analysis on a database of 1.3 million users, resulting in targeted marketing campaigns that increased conversion rates by 20%. • Analysed and cleansed a data warehouse with over 450 million lines spanning 3 years using SQL on Big Query and visualised the results in Power BI. • Orchestrated a team transformation by assigning roles based on strengths and promoting a culture of collaboration, resulting in a 30% increase in productivity and a 40% reduction in project bottlenecks.

Education

2025 - 2028

BSc Data Science at Lancaster University

2024-2025

Foundation in Maths and Computer Science

Achieved a first class