At a Glance
- Tasks: Analyse data to drive commercial performance and influence strategic decisions.
- Company: A leading consumer-focused organisation embracing data and AI transformation.
- Benefits: Hybrid working, autonomy, and a chance to shape analytics strategy.
- Other info: Collaborative culture with opportunities for professional growth and innovation.
- Why this job: Make a real impact on business outcomes with innovative analytics and AI.
- Qualifications: Experience in data analysis, strong SQL skills, and a degree in a numerical discipline.
The predicted salary is between 45000 - 55000 £ per year.
We’re working with a highly recognised consumer-focused organisation undergoing an exciting transformation in how it uses data, analytics and AI to drive commercial performance. This is a newly enhanced opportunity for a commercially minded Data Science Analyst to play a pivotal role in shaping strategic decisions across multiple revenue streams, products and customer journeys.
This is far more than a reporting role. You’ll sit at the intersection of commercial strategy, advanced analytics and AI-driven insight — partnering closely with senior stakeholders to influence pricing, forecasting, customer retention, revenue optimisation and long-term growth.
Joining a growing commercial analytics function, you’ll help evolve the organisation’s capability from traditional reporting into predictive, insight-led decision making. You’ll work across a broad range of commercial areas including customer membership, digital products, travel and leisure services, financial products and customer loyalty — using data to unlock growth opportunities and improve customer lifetime value.
The role offers a genuine chance to shape the future analytics roadmap, introduce modern data science techniques and champion AI adoption across the wider business.
What You’ll Be Doing
- Delivering commercially focused analysis and actionable insight to senior stakeholders
- Building predictive models to support customer retention, acquisition and propensity analysis
- Developing forecasting models for demand, occupancy, revenue and performance trends
- Creating dashboards and performance reporting that drive strategic decision making
- Conducting root-cause analysis to identify opportunities, risks and commercial drivers
- Supporting pricing, promotions and scenario modelling initiatives
- Working with large and varied datasets across multiple systems and business functions
- Driving AI and automation initiatives to improve insight generation and operational efficiency
- Helping shape best practice around data quality, governance and analytics capability
What We’re Looking For
We’re looking for someone who combines strong technical capability with genuine commercial curiosity. You’ll likely have experience in a commercial analytics, data science or insight-focused role where you’ve worked closely with business stakeholders and translated complex data into meaningful action.
Key Skills & Experience
- Strong SQL and advanced data manipulation skills
- Experience using Python or R for predictive modelling and machine learning
- Knowledge of models such as Random Forest, XGBoost or similar
- Strong BI and dashboarding capability (Tableau, Power BI or similar)
- Advanced Excel modelling and scenario analysis skills
- Experience with forecasting, segmentation or propensity modelling
- Ability to communicate complex insights clearly to non-technical audiences
- Commercial awareness and an understanding of business performance drivers
- Interest or experience in AI/LLM technologies and automation
- Degree educated in a numerical discipline such as Data Science, Statistics, Mathematics, Economics or Physics
Why This Role Stands Out
- Opportunity to influence commercial strategy at a senior level
- Broad, varied analytics environment with real business impact
- Strong focus on innovation, predictive analytics and AI
- High visibility across multiple commercial functions
- Opportunity to help shape and modernise the organisation’s data capability
- Hybrid working and collaborative culture
- Genuine autonomy and ownership
If you’re looking for a role where you can combine commercial thinking, advanced analytics and modern AI-driven insight to influence real business outcomes, we’d love to hear from you.
Data Analyst in Crawley employer: James Chase
Join a forward-thinking organisation that values innovation and collaboration, offering a dynamic work environment where your insights will directly influence commercial strategy. With a strong focus on employee growth, you will have the opportunity to develop your skills in advanced analytics and AI while working alongside senior stakeholders across diverse business functions. Enjoy the benefits of hybrid working and a culture that champions autonomy and ownership, making this an excellent place for those seeking meaningful and impactful employment.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst in Crawley
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even casual coffee chats. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Show Off Your Skills
Create a portfolio showcasing your data analysis projects. Use platforms like GitHub to share your code and visualisations. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Ace the Interview
Prepare for interviews by practising common data analyst questions and scenarios. Be ready to discuss your past experiences and how they relate to the role. Remember, it’s not just about your technical skills; show your commercial awareness too!
✨Apply Through Our Website
Don’t forget to check out our website for the latest job openings! Applying directly through us can give you an edge, as we love seeing candidates who are proactive and genuinely interested in joining our team.
We think you need these skills to ace Data Analyst in Crawley
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Data Analyst. Highlight your experience with SQL, Python, and any predictive modelling you've done. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're excited about this opportunity and how your commercial curiosity can drive insights. Let us know how you can influence strategic decisions!
Showcase Your Projects:If you've worked on relevant projects, don’t hold back! Share examples of dashboards you've created or predictive models you've built. We love seeing real-world applications of your skills!
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you get all the updates. Plus, it shows you're keen on joining our team!
How to prepare for a job interview at James Chase
✨Know Your Data Inside Out
Before the interview, dive deep into the data analytics tools and techniques mentioned in the job description. Brush up on your SQL skills and be ready to discuss how you've used Python or R for predictive modelling. Being able to talk confidently about your experience with models like Random Forest or XGBoost will definitely impress.
✨Showcase Your Commercial Acumen
This role is all about influencing commercial strategy, so make sure you can articulate how your analytical insights have driven business decisions in the past. Prepare examples where your work has directly impacted customer retention or revenue optimisation, and be ready to discuss how you can bring that same value to their organisation.
✨Prepare for Scenario-Based Questions
Expect questions that ask you to solve real-world problems using data. Think about how you would approach forecasting demand or conducting root-cause analysis. Practising these scenarios will help you demonstrate your problem-solving skills and your ability to think critically under pressure.
✨Communicate Clearly and Confidently
You’ll need to explain complex insights to non-technical stakeholders, so practice simplifying your explanations. Use clear, concise language and avoid jargon. Consider preparing a few key points or stories that illustrate your ability to translate data into actionable insights, as this will show your communication prowess.
