Work preference
Job search status:
Desired job title
Location preference
Location:
Open to relocation:
Minimum Desired Compensation
Results-oriented data analytics professional with expertise in managing complex analytics projects and delivering insights through advanced SQL, Python, and Excel. Utilises AI-assisted tools for predictive modelling and data storytelling across platforms like Power BI, Tableau, and Looker Studio. Collaborates with cross-functional teams to align objectives and uphold data standards, driving commercial improvements through evidence-based decision-making.
Work history
Data Analyst
5 Months- Analysed environmental and operational datasets using SQL and Python to support waste management and sustainability initiatives.
- Leveraged AI-assisted analysis tools to discover patterns and identify optimisation opportunities in waste stream data.
- Developed and maintained Power BI dashboards monitoring KPIs such as collection adherence, contamination rates, and material repurposing performance.
- Produced benchmarking and trial analysis reports that improved recycling accuracy by 15%.
- Partnered with product, engineering, and account management teams to analyse client trial outcomes and identify key drivers of platform adoption.
Business Intelligence Analyst
3 Years 2 Months- Executed complex SQL queries and automated ETL processes to integrate data from sales, procurement, and inventory systems, enhancing data accessibility for analysis.
- Analysed historical supply chain data using statistical methods and AI-powered tools to identify operational bottlenecks and improve inventory planning.
- Produced performance reports for senior leadership, highlighting KPIs such as turnover, cost per metric ton, and inventory turnover ratio, enabling informed decision-making.
- Conducted margin and cost analysis, supporting pricing and profitability optimization.
Teacher of Mathematics & Statistics
9 Years 5 Months- Delivered curriculum-aligned mathematics and statistics instruction with a focus on numerical reasoning and data literacy.
- Evaluated teaching strategies using data-driven approaches to identify effective practices and enhance student learning outcomes.
- Analysed and reported assessment data to track student performance and inform targeted interventions, enhancing support for individual learning needs.
Education
MSc - Data Science & Artificial Intelligence
Enter your degree - Data Science & Business Analytics
ACCA Diploma - Accounting and Business (RQF Level 4)
Bachelor of Science with Education - Mathematics & Statistics
Skills
- Data Analysis & Programming: SQL (Advanced)
- Python
- Excel (Advanced)
- Business Intelligence & visualisation: Power BI (Expert)
- Looker Studio
- Tableau
- Data Storytelling
- Statistical Analysis
- AI data analysis
- Cloud & Data Infrastructure: Google BigQuery
- Databricks
- Google Sheets
- Google Drive
- Data-driven decision making
- Project management
- Collaboration: Works effectively within cross-functional teams (product engineering
- account management) to align objectives
- drive platform adoption
- and ensure consistent data standards.
- Stakeholder communication
- Creative problem solving
- AI data analysis
- context analysis
- analyses using Hex
Certification
- Databricks Academy – Data Engineering with Databricks
- Power BI for Business Intelligence | Tableau for Data Analytics & Business Intelligence
- IBM Professional Certificate in Data Science
- Google Cloud Platform – BigQuery & Data Analytics | Looker and Looker Studio
- Google Sheets Advanced | AI-Assisted Data Analysis Tools & Techniques
Work availability
PROJECT PORTFOLIO
My project portfolio comes from a structured data science programme with Great Learning, completed between May and October 2024. Each project was built around a real business problem, taking me from exploratory analysis to tuned machine learning models.
I began with FoodHub, using Python to analyse food delivery orders and answer operational questions. In E-news Express, I used hypothesis and A/B testing to judge whether a redesigned landing page improved subscriber conversion, and whether conversion depended on the reader’s preferred language.
For ReCell, I built a linear regression model to support dynamic pricing of refurbished devices, checking the model’s assumptions before drawing conclusions. INN Hotels involved predicting booking cancellations with logistic regression and pruned decision trees, using ROC-AUC to select a model that could inform refund policy. In EasyVisa, I compared bagging, random forest, boosting and stacking classifiers, tuned with GridSearchCV, to identify the factors driving visa approval.
The project closest to my professional interests was ReneWind, which used turbine sensor data to predict generator failures before they occur. Because failures were rare, I handled class imbalance through resampling, alongside regularisation and hyperparameter tuning. The aim was to catch faults early and cut maintenance costs, which links directly to my background in sustainability analytics.
I finished with Trade&Ahead, grouping stocks through K-means and hierarchical clustering and profiling each cluster to explain what set them apart.
Across all seven projects, the common thread was turning results into recommendations a business could act on. That is the part of the work I enjoy most, and what I bring to my role as a data analyst.