At a Glance
- Tasks: Own performance reporting and analyse subscriber behaviour to drive retention strategies.
- Company: Join a globally recognised household name in the Customer Intelligence team.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Urgent role with quick interviews and a smooth two-stage process.
- Why this job: Make a real impact by transforming data into strategic insights for customer retention.
- Qualifications: 4-6 years in data analytics with experience in subscription businesses.
The predicted salary is between 39600 - 48400 £ per year.
A Global Well Known household name is hiring a Senior Data Analyst into its Customer Intelligence team.
Job Description:
- Own the weekly performance reporting - subscriber base movement, churn cohorts, CRM campaign incrementality, payments recovery.
- Maintain a standing view of subscriber behaviour across lifecycle stage, acquisition channel, offer type and engagement, by market.
- Spot material shifts in cohort behaviour before they show up in aggregate churn.
- Act as the primary client of the central Data & Insights team - set the analytical agenda, write the briefs, turn what comes back into retention intelligence.
- Run the Voice of Customer programme, and surface where qualitative feedback contradicts what the behavioural data says.
- Feed the 12-week rolling forecast and cohort LTV model.
Requirements:
- 4-6 years in data analytics, business intelligence or performance insight.
- Experience in a subscription business - SaaS, media, telecoms or digital subscriptions.
- Predictive modelling, cohort analysis and behavioural segmentation, hands-on.
- Deep understanding of retention metrics: churn forecasting, cohort LTV, lifecycle stages, acquisition channel performance.
- Proven at moving beyond reporting into strategic recommendations.
- Experience commissioning work from a central data team through well-defined briefs.
- Comfortable presenting to Director and C-suite stakeholders.
- Voice of Customer experience - integrating qualitative feedback with behavioural data.
Please only apply if you have full working UK Rights as there is no sponsorship on offer. This is an Urgent role with interviews happening next week and a smooth two stage interview process.
Senior Data Analyst employer: We Source Talent
Join a pioneering AI-native property platform that is not only backed by significant investment but also fosters a dynamic and innovative work culture. As an early core member, you'll have the opportunity to shape the future of agentic systems while enjoying robust employee growth opportunities, a collaborative environment, and the chance to make a meaningful impact in the rapidly evolving AI landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Analyst
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like We Source Talent!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Data Analyst at We Source Talent.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like We Source Talent.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Data Analyst at We Source Talent, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Data Analyst
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 We Source Talent, 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 We Source Talent. 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 We Source Talent
✨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 We Source Talent!
✨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.
