At a Glance
- Tasks: Analyse customer behaviour and turn data into actionable insights for business growth.
- Company: Join a leading retail brand focused on customer experience and innovation.
- Benefits: Enjoy 40% staff discount, private healthcare, and extra leave on your birthday!
- Other info: Collaborative culture with opportunities for continuous learning and career advancement.
- Why this job: Make a real impact by driving data-driven decisions in a dynamic environment.
- Qualifications: 3+ years in analytics with skills in SQL, Python, or R required.
The predicted salary is between 49500 - 60500 £ per year.
The Role
Utilise advanced analytical techniques to understand customer behaviour, identify opportunities across acquisition, retention, loyalty and customer value, and turn data into recommendations that improve business decision-making.
Whats in it for you
- 40% staff discount plus friends & family discounts throughout the year
- Access to our reward platform for external discount and offers
- Private pension scheme
- Virtual GP access for you and your children - it allows you to speak to a doctor at a time and date that suits you
- All employees are covered by our life assurance policy from day one
- Unlock extra leave with our buy more holiday scheme
- Celebrate YOU! Enjoy an extra paid day off on your birthday each year
- Enhanced maternity, paternity and adoption leave, and shared parental leave (eligible after 2 years' service)
- Spread the cost of your commute with interest-free season ticket loans
- Do your bit for the environment and save money with our Cycle2Work scheme
- We're proud to partner with the Retail Trust and Fashion & Textile Children's Trust
What you'll be doing
- Data
Mining: Use data mining techniques to combine multiple large customer, transaction, campaign and digital datasets into new data marts, analytical models and reusable insight assets.
- Descriptive
Analytics: Interpret data and present findings to stakeholders in a clear and impactful manner to drive data-driven decision making.
Deliver deep-dive customer insight and recommendations that explain customer performance and behavioural trends.
- Advanced
Analytics: Apply statistical and analytical techniques such as segmentation, clustering, predictive modelling and campaign measurement.
Working knowledge of data science techniques including random forest, k-means and linear regression.
- Optimisation: Collaborate with cross-functional teams to identify opportunities for optimisation.
Support initiatives across customer acquisition, retention, loyalty, lifecycle and marketing performance.
- Collaborate: Support a given analytical principle and deliver an agreed analytics strategy.
Create stakeholder-ready dashboards, reporting and insight packs while ensuring outputs are accurate, documented and governed.
- Development: Stay updated on industry trends and best practices in customer analytics, loyalty, CRM, marketing measurement and analytical techniques.
- Analytical mindset: Customer-focused mindset with the ability to think critically, challenge assumptions and solve complex business problems through data.
- Attention to detail: Ensure accuracy, consistency and reliability of analytical findings, maintaining high standards of quality and governance.
- Commercial curiosity: Demonstrate a strong interest in customer behaviour and how it impacts sales, loyalty, retention, profitability and long-term customer value.
- Clear communicator: Translate complex analytical concepts and findings into clear, impactful recommendations for both technical and non-technical stakeholders.
- Continuous learning: Proactively seek opportunities to expand analytical, technical and customer knowledge, staying up to date with emerging best practices.
- Strong Opinions Loosely Held: Be vocal and maintain your point of view while remaining open to new ideas, challenge and opposing perspectives.
Who you are
- Proficiency in statistical analysis, customer analytics and data visualisation tools. Experience working with large customer, marketing, loyalty or digital datasets. (3+ years)
- Proven experience writing code in languages such as SQL, Python or R.
- Experience applying advanced analytical techniques including segmentation, regression analysis, clustering, predictive modelling and campaign measurement.
Knowledge of data science and machine learning techniques such as random forest, k-means and linear regression.
- Strong communication, presentation and data storytelling skills, with the ability to translate complex analytical findings into clear and commercially relevant recommendations.
- Good understanding of customer profiling, customer value, customer lifecycle measurement and behavioural analytics.
- Experience creating stakeholder-ready dashboards, reporting solutions and insight packs using data visualisation tools.
- Knowledge of data quality, governance, documentation standards and ethical use of customer data.
Insight quality and impact. Timely delivery. Stakeholder satisfaction. Adoption of customer insights and outputs. Development of analytical capability.
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Senior Analyst – Customer Health in London employer: Stryker Corporation
Stryker Corporation is an exceptional employer that fosters a dynamic and inclusive work culture, offering employees the chance to thrive in a remote setting while being part of a leading medical communications team. With a strong emphasis on professional development and growth opportunities, employees are encouraged to enhance their skills and advance their careers, all while contributing to meaningful projects that impact healthcare globally.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Analyst – Customer Health in London
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We think you need these skills to ace Senior Analyst – Customer Health 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 Stryker Corporation, 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 Stryker Corporation. 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 Stryker Corporation
✨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 Stryker Corporation!
✨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.
