At a Glance
- Tasks: Shape data-driven decisions and drive commercial performance with analytics.
- Company: A customer-focused organisation undergoing a major transformation.
- Benefits: Up to £89,000 salary, 10% bonus, and hybrid working model.
- Other info: Collaborative environment with opportunities for growth across digital and physical channels.
- Why this job: Join a high-impact role influencing senior leadership and shaping analytics capabilities.
- Qualifications: Experience with SQL, Python, and customer analytics required.
The predicted salary is between 89000 - 89000 £ per year.
This is an exciting opportunity to join a highly visible analytics function during a major business transformation. You will play a key role in shaping how data is used to drive commercial performance, working closely with senior stakeholders across digital, retail, and strategy.
The Company
They are a large, customer‑focused organisation operating across both digital and physical channels, currently undergoing significant transformation. With a strong emphasis on data‑led decision making, they are investing heavily in analytics to unlock commercial growth and improve customer outcomes. The business fosters a collaborative environment where analytics is central to strategic planning. You will join a team that is evolving its capabilities and influence across the organisation.
The Role
You will sit within a central insight and analytics function, acting as a bridge between data and commercial decision making. Key responsibilities include:
- Working with large, complex datasets to generate actionable insights using SQL and Python
- Translating analysis into clear, commercially relevant recommendations for stakeholders
- Supporting KPI reporting and developing scalable dashboards using Power BI
- Designing and evaluating A/B tests to optimise business performance
- Delivering customer and marketing analytics, including segmentation, cohort analysis, and lifetime value modelling
- Partnering with digital, retail, finance, and strategy teams to influence decision making
- Improving reporting frameworks, metric consistency, and data quality processes
- Navigating ambiguity and incomplete data to provide pragmatic, insight‑led solutions
Your Skills & Experience
- Strong commercial experience with SQL and the ability to work with large, complex datasets
- Experience using Python or similar tools for analysis and automation
- Proficiency in Power BI or other dashboarding tools
- Background in customer or marketing analytics, including segmentation and test and learn methodologies
- Ability to translate data into clear business recommendations and influence stakeholders
- Experience working across multiple data sources in complex environments
- Strong analytical thinking with a proactive and collaborative approach
What They Offer
- Salary up to £89,000 plus 10% bonus
- Hybrid working model with flexibility
- High-impact role with exposure to senior leadership
- Opportunity to shape analytics capabilities within a transforming business
- Broad cross‑functional exposure across both digital and physical channels
- A collaborative environment that supports growth and development
StudySmarter Expert Advice🤫
We think this is how you could land Portfolio Analytics Manager
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We think you need these skills to ace Portfolio Analytics Manager
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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How to prepare for a job interview at Harnham
✨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
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✨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.
