At a Glance
- Tasks: Transform complex data into actionable insights and develop intuitive dashboards.
- Company: Join Mastercard, a leader in digital payments and innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on collaboration and continuous learning.
- Why this job: Make an impact by turning data into insights that drive business decisions.
- Qualifications: Experience in data analysis with strong skills in Python and SQL.
The predicted salary is between 37800 - 46200 £ per year.
Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide.
Together with our customers, we’re helping build a sustainable economy where everyone can prosper.
We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible.
Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
Title and Summary Analyst, Data Analytics We are looking for a highly analytical and technically capable BI/Data Analyst to join our team.
You will turn complex data into clear, actionable insights that support better business decisions.
This role combines business intelligence, advanced analytics and data storytelling.
You will work closely with stakeholders to understand business challenges, use SQL and Python to explore and analyze data, and build scalable reporting and analytical solutions using Power BI and Microsoft Fabric.
Key Responsibilities Analyze large and complex datasets to identify trends, drivers, anomalies and opportunities.
Use Python and SQL for data manipulation, advanced analysis, automation and analytical modelling.
Design and develop intuitive dashboards and reporting solutions using Power BI.
Work within Microsoft Fabric to access, transform, analyse and deliver data and insight.
Partner with stakeholders to translate business challenges into meaningful analytical questions, metrics and KPIs.
Conduct deep-dive and root-cause analysis to understand what is happening, why it is happening and where action should be taken.
Develop repeatable and scalable analytical solutions rather than relying on manual analysis.
Communicate complex findings through clear visualisations, data storytelling and recommendations.
Support data quality, governance, documentation and consistent reporting standards.
Requirements Proven experience in a BI, Data Analyst or similar analytical role.
Strong Python skills for data analysis, automation and statistical modelling.
Strong SQL skills and experience working with large and complex datasets.
Hands-on experience with Microsoft Fabric and its data and analytics capabilities.
Strong experience developing dashboards and analytical solutions in Power BI.
Experience applying advanced analytical techniques such as statistical analysis, forecasting, segmentation, cohort analysis, anomaly detection or driver analysis.
Good understanding of data modelling, data warehousing and ETL processes.
Strong problem-solving skills and the ability to turn ambiguous business questions into structured analysis.
Excellent communication and data storytelling skills, with the ability to explain complex analysis to non-technical audiences.
Nice to Have Experience with cloud platforms such as Azure.
Experience developing automated or scalable analytical solutions.
Exposure to machine learning or predictive analytics.
Degree or equivalent experience in Mathematics, Statistics, Computer Science, Data Science or another quantitative discipline.
All About You You are naturally curious and want to understand why something is happening, not simply report that it has happened.
You enjoy working with complex data, testing hypotheses and finding patterns others might miss.
You are comfortable moving between Python, SQL, Fabric and Power BI, but understand that technology is only part of the role.
Most importantly, you can turn data into insight, understanding and action.
Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.
Job Summary Job number: R-288700Date posted : 2026-11-04Profession: AI & Data Employment type: Full time
Analyst, Data Analytics employer: MasterCard
Mastercard is an exceptional employer that fosters a culture of innovation and collaboration, making it an ideal place for a Director of Software Engineering. With a strong emphasis on employee growth, you will have access to cutting-edge tools and resources, as well as opportunities to mentor and lead talented teams across diverse geographies. The company's commitment to data-driven decision-making and AI-assisted development ensures that you will be at the forefront of technological advancements in a dynamic and supportive environment.
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We think this is how you could land Analyst, Data Analytics
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Analyst, Data Analytics
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at MasterCard, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at MasterCard. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at MasterCard
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at MasterCard!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
