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Data Analyst with 2+ years in SQL, Power BI & Machine Learning
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Data analyst with an MSc in Data Science & Analytics from the University of Leeds and hands-on experience turning data into clear, decision-ready insight. Strong in SQL (MySQL, PostgreSQL), Power BI and Excel, with a track record of building reporting suites, automating manual workflows and explaining findings to non-technical stakeholders. Experienced across pricing, occupancy and revenue analytics, forecasting and segmentation, and comfortable owning analysis from messy raw data through to a recommendation people can act on. Full UK right to work and open to relocation.
University of Leeds
MSc · Data Science & Analytics
August 1, 2023 – June 30, 2024
Nowrosjee Wadia College, Pune University
BSc · Computer Science
August 1, 2019 – June 30, 2022
Let Sell Properties
Data Analyst Intern
June 1, 2025 – Present
London, England, United Kingdom
University of Leeds
Junior Data Analyst
May 1, 2024 – August 1, 2024
Leeds, England, United Kingdom
Meat Stack
Manager
December 1, 2023 – June 1, 2025
Leeds, England, United Kingdom
Time Series Forecasting & Sentiment Analysis
September 1, 2023 – September 1, 2024
Benchmarked ARIMA, ETS and Drift models on consumer-expenditure data to minimise RMSE/MAE; built sentiment-trend dashboards from 3,000+ reviews that informed operational and marketing decisions.
Voice of Customer Analytics Platform
September 1, 2023 – September 1, 2024
End-to-end pipeline over 24,611 customer contacts: intent classification (weighted F1 0.995), sentiment and topic analysis, and semantic search; surfaced through a Streamlit dashboard with automatic summaries from a locally-hosted LLM, quantifying a 52.5% automation opportunity.
Dynamic Pricing Engine for Holiday Rentals
September 1, 2023 – September 1, 2024
Built an end-to-end dynamic pricing prototype on ~4,900 holiday-rental listings: cleaned and labelled messy data (with root-cause fixes for placeholder prices and mislabelled listings), derived occupancy and demand from booking calendars, segmented properties into pricing tiers with K-Means, forecast demand and seasonality with Prophet, and trained a price-recommendation model (random forest vs linear baseline, ~20% lower error), combined with a seasonal multiplier for dynamic prices.
Robot Selection & Logistics Optimisation
September 1, 2023 – September 1, 2024
Applied multi-criteria decision analysis (TOPSIS) across 8 dimensions plus a constraint-based allocation model; delivered a recommended configuration and cost-benefit dashboards for management.
Statistical Analysis of Dog-Adoption Trends
September 1, 2023 – September 1, 2024
Used Kolmogorov-Smirnov, Z- and T-tests and distribution modelling to identify breed-level differences in rehoming time, translating the findings into targeted recommendations to reduce waiting times.
Automated News Scraping & Text Analytics Dashboard
September 1, 2023 – September 1, 2024
Built an ETL pipeline ingesting 500+ articles a day via Newspaper3k/Feedparser, transforming unstructured text into structured, dashboard-ready data with word clouds and sentiment trends for editorial decision-making.
Robot Selection & Logistics Optimisation
September 1, 2023 – September 1, 2024
Applied multi-criteria decision analysis (TOPSIS) across 8 performance dimensions, then built linear-programming allocation models respecting budget and availability; delivered a recommended configuration, deployment schedule and cost-benefit dashboards for management (efficiency improved ~22%).
Microsoft Excel 2019 Associate Certification
Microsoft
June 1, 2026 – Present
Google Data Analytics Professional Certificate
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic background in Data Science & Analytics and Computer Science, coupled with diverse project experience (e.g., dynamic pricing, sentiment analysis, logistics optimization, voice of customer analytics), indicates a broad interest in data-driven problem-solving. Their willingness to relocate and work in various settings (on-site, hybrid, remote) suggests flexibility. The blend of academic rigor and practical application aligns well with a data-driven culture that values continuous learning and impactful solutions.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through various projects tackling real-world scenarios like dynamic pricing and logistics optimization. Their experience in training colleagues on reporting tools and presenting findings to academic stakeholders indicates good communication and collaboration skills. The manager role at Meat Stack, while not directly technical, suggests operational awareness, responsibility, and the ability to manage tasks and improve processes.