At a Glance
- Tasks: Transform complex fan data into actionable insights for sports marketing.
- Company: Join a leading global data and AI company with a focus on innovation.
- Benefits: Competitive salary, private healthcare, bonuses, and professional development opportunities.
- Other info: Flexible hybrid working model and a commitment to diversity.
- Why this job: Combine your passion for sports with data analysis to drive real impact.
- Qualifications: 2-5 years of analytics experience and strong SQL and Python skills required.
The predicted salary is between 37800 - 46200 £ per year.
Description
EXL (NASDAQ: EXLS) is a global data and artificial intelligence ("AI") company that offers services and solutions to reinvent client business models, drive better outcomes and unlock growth with speed.
EXL harnesses the power of data, AI, and deep industry knowledge to transform businesses, including the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others.
EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect.
We are headquartered in New York and have more than 60,000 employees spanning six continents. For more information, visit www. exlservice. com .
Role Title
Data Analyst
BU/Segment
Analytics
Location
London, United Kingdom (Hybrid working 3 days a week in the client office)
Employment Type
Permanent
Summary of the role
EXL is looking for a Data Analyst with a passion for sports who will play a key role in providing analytics support to a client within our Sports, Media and Entertainment practice.
Based in London, the role sits within the International Fan Data & Analytics team, supporting fanbase growth and engagement across international markets.
The primary responsibility of this role is to turn large, complex fan datasets into clear insights that help business stakeholders make better decisions.
Working hands-on with SQL, Python and cloud data platforms such as Databricks, AWS and Snowflake, you will build the analysis, reporting and audience segments that power international marketing campaigns and track performance against growth goals.
You will work with a dynamic team and will have real ownership of, and impact on, the analysis and data products you deliver.
The ideal candidate brings 2–5 years of analytics experience, strong technical skills and an understanding of the fan lifecycle, combined with the ability to translate business questions into well-structured analysis, explain findings clearly to non-technical audiences, and work closely with marketing, international and data engineering teams to deliver measurable value.
If you’re a passionate sports fan who enjoys solving problems with data – and you thrive in fast-paced, collaborative environments – we’d love to connect.
As part of your duties, you will be responsible for
- Data Analysis
- Write efficient SQL and Python to extract, clean, transform and analyse large fan and marketing datasets.
- Work within cloud data platforms (Databricks, Snowflake, AWS) to build and maintain analytical datasets and workflows.
- Take a business question, develop an analysis plan, and deliver an answer that addresses it.
- Summarise large data outputs into clear, business-friendly takeaways for stakeholders.
- Reporting & Performance Tracking
- Build and maintain dashboards and recurring reports on fan growth, engagement and lifecycle metrics across international markets.
- Monitor campaign and go-to-market (GTM) performance using agreed KPIs and success criteria.
- Contribute to regular performance updates for team leads and senior stakeholders.
- Campaign & Audience Enablement
- Prepare audience segments and data for 1:1 marketing campaigns, including test/control groups.
- Support segmentation analysis that helps regional teams deepen fan engagement in local markets.
- Data Quality & Collaboration
- Support user acceptance testing (UAT) of database changes and updates.
- Help data engineering teams with root cause analysis (RCA) of data issues and bugs.
- Work with marketing, international and data engineering teams to gather and document business requirements.
- Liaise with third-party partners on data needs and definitions.
- Qualifications and experience we consider to be essential for the role:
- Bachelor’s degree in Analytics, Computer Science, Statistics, Economics, Business or a related field, or equivalent experience.
- 2–5 years of experience in a data analyst or similar role.
- Strong SQL skills, including complex joins, aggregations and window functions.
- Proficiency in Python for data analysis (e. g., pandas, Num Py).
- Hands-on experience with at least one cloud data platform: Databricks, AWS or Snowflake.
- Strong analytical and problem-solving skills, with close attention to detail.
- Ability to explain technical findings clearly to non-technical audiences
Skills and Personal attributes we would like to have
- Experience with BI and visualisation tools (e. g., Tableau, Power BI, Looker).
- Experience in marketing, CRM or customer analytics.
- Knowledge of consent management, identity resolution or UK GDPR.
- Experience in a consulting or client-facing environment.
- Passion for sport and an understanding of global fan cultures.
- As part of a leading global Data and AI company, you can look forward to:
- A competitive salary with a generous bonus, private healthcare, critical illness life assurance at 4 x your annual salary, income protection insurance, and a rewarding pension.
- EXL provides everyday financial well-being solutions, such as cash back cards, in which you can earn cashback while enjoying discounts, promotions, and offers from top retailers.
We also offer a Cycle Scheme where you can save money on bikes and cycling accessories.
- At EXL, we are committed to providing our employees with the tools and resources they need to succeed and excel in their careers.
We offer a wide range of professional and personal development opportunities.
We also support a range of learning initiatives that allow our employees to build on their existing skills and knowledge.
From online courses to seminars and workshops, our employees have the opportunity to enhance their skills and stay up to date with the latest trends and technologies.
- As an Equal Opportunity Employer, EXL is committed to diversity.
Our company does not discriminate based on race, religion, colour, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, age, or disability status.
- EXL employees are eligible to purchase stock as part of our Employee Stock Purchase Plan (ESPP).
- At EXL, we offer a flexible hybrid working model that allows employees to live a balanced, healthy lifestyle while strengthening our culture of collaboration.
To be considered for this role, you must already be eligible to work in the United Kingdom.
Data Analyst in London employer: EXL
EXL is an exceptional employer that fosters a dynamic and inclusive work culture, offering employees the chance to thrive in a fast-paced fintech environment. With a strong focus on professional development, team collaboration, and innovative problem-solving, employees are empowered to grow their skills while contributing to meaningful projects in regulatory reporting and compliance. The remote working flexibility allows for a balanced lifestyle, making EXL an attractive choice for those seeking rewarding career opportunities in the UK.
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We think this is how you could land Data Analyst in London
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Data Analyst in London
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!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at EXL, 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 EXL. 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 EXL
✨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!
✨Showcase Your Projects
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 EXL!
✨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.
