Data Analyst
Role details
Job location
Tech stack
Job description
Join us to help keep even more people and pets together when times are tough. For over a century, PDSA have provided vital veterinary care for the pets of people in financial hardship.
We're now on a journey to expand our reach to support even more people and their beloved pets. To achieve this ambitious goal, we need passionate and driven individuals who are ready to embrace change and help shape a future-focused PDSA. Together, we'll build a stronger organisation to ensure our services help those who need us most for the next hundred years.
If you're ready to make a real difference and be part of a team that's creating positive change, we want you to join us. Let's build a brighter future for pets and their owners, together.
The successful candidate will work closely with marketing, fundraising, and data teams to turn complex datasets into clear, actionable insights that support growth and improve performance across channels.
As Data Analyst, you will:
Data Collection & Analysis - Gather, interpret, and analyse data from multiple sources to provide actionable insights that support organisational strategy and operational efficiency.
Data Cleaning & Preparation - Preprocess and clean datasets to eliminate inconsistencies and errors, ensuring data integrity for accurate analysis.
Statistical Analysis & Trend Identification - Apply statistical techniques and exploratory data analysis (EDA) to identify trends, patterns, and insights within datasets.
Data Visualisation & Reporting - Design dashboards, reports, and visualisations using Count (similar to Power BI, Tableau etc) to present complex data in a user-friendly format.
Stakeholder Collaboration - Work closely with business stakeholders to understand data needs, provide analytical support, and enable data-driven decision-making.
Database/Data Warehouse Management & Optimisation - Collaborate with Data Engineering to develop and optimise our data platforms, acquire new data, optimise data structures, and ensure efficient data retrieval methods for analysis and reporting.
Requirements
Technical Proficiency - Strong knowledge of data analysis tools, including Excel, SQL, Python, Data Visualisation (e.g. Count, Tableau, Power BI).
Statistical & Analytical Expertise - Understanding of statistical methods, data modelling, and problem-solving techniques to extract meaningful insights.
Data Accuracy & Integrity - Ability to identify and resolve discrepancies in datasets to ensure high-quality and reliable analysis.
Data Visualisation & Communication - Ability to translate complex data into clear, visually appealing reports for business stakeholders.
Collaboration & Business Understanding - Experience working with cross-functional teams to align data insights with business goals.
Data Governance & Best Practices - Knowledge of data governance, documentation standards, and industry best practices in data management.
Applicants need a background in marketing/CRM/customer/audience/loyalty analytics, producing analysis and insights to understand performance, behaviour and shape strategy.