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- Tasks: Dive into data to enhance customer marketing strategies and drive impactful campaigns.
- Company: Join a leading B2C fintech with a massive consumer database of over 30 million customers.
- Benefits: Enjoy hybrid working, competitive salary, bonuses, pension, healthcare, and more perks.
- Why this job: Be part of a dynamic team in a fast-paced, supportive environment focused on consumer advocacy.
- Qualifications: Experience in CRM analytics, strong SQL and Python skills, and a passion for data storytelling required.
- Other info: Work closely with data engineers and be the go-to expert for customer and campaign data.
The predicted salary is between 40000 - 46000 £ per year.
Location: Hybrid working, Central London offices, 10 days in every month.
Salary: £50,000 - £55,000 plus 10% bonus, pension, healthcare, life assurance, etc.
You’ll be joining an 800 person B2C fintech which has one of the largest consumer databases in the UK, made up of over 30m customers. The team you’ll be joining is their CRM division, and the projects you’ll be working on all align to customer marketing initiatives.
- Looking at creative use and application of data in a marketing context.
- Making recommendations on how to improve targeting by looking at past performance of campaigns.
- Working on the application and deployment of data science solutions such as ML and next best action models.
- Identifying new data assets either already within the business or via third party partnerships.
- Driving personalisation and identifying new potential trigger points within the customer lifecycle.
- Utilising data to enrich targeting strategies for existing campaigns.
You will be the subject matter expert on customer and campaign data, ensuring the right data is available to the CRM team to deliver a best in class customer marketing programme. This role covers multiple disciplines including data planning, CRM analytics, decision science, and data science.
From a technical perspective, a solid stats background with a good handle on SQL and Python coding skills is required, along with experience analysing large relational databases. A natural curiosity about customer behaviour and CRM campaigns is essential.
Experience Needed:
- A CRM or marketing related analytics background is essential.
- Knowledge of segmentations, logistic regression, and predictive analytics.
- Solid analytics skills with the ability to identify trends and generate meaningful insights.
- Hands-on SQL and Python skills with experience of working with Cloud warehouses like Redshift.
- Comfortable in fast-paced environments like retail, digital, or tech.
This opportunity is appealing due to the people, environment, and the employer brand itself. The employer is known for its ambition to do good by the consumer while achieving success for themselves.
Data Scientist, Customer Marketing employer: Blue Pelican
Contact Detail:
Blue Pelican Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist, Customer Marketing
✨Tip Number 1
Familiarise yourself with the latest trends in CRM analytics and customer marketing. Understanding current strategies and tools used in the industry will help you speak confidently about how you can contribute to the team.
✨Tip Number 2
Network with professionals in the fintech and data science sectors. Attend relevant meetups or webinars to connect with people who work in similar roles, as they might provide insights or even referrals that could help you land the job.
✨Tip Number 3
Brush up on your SQL and Python skills by working on real-world projects or contributing to open-source initiatives. Being able to demonstrate your technical capabilities through practical examples can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss your analytical approach to customer behaviour and campaign performance. Think of specific examples where you've successfully identified trends and made recommendations based on data insights, as this will showcase your problem-solving skills.
We think you need these skills to ace Data Scientist, Customer Marketing
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in CRM analytics and data science. Emphasise your skills in SQL and Python, as well as any projects where you've applied predictive modelling or customer segmentation.
Craft a Compelling Cover Letter: In your cover letter, express your passion for customer marketing and data analysis. Mention specific examples of how you've used data to drive marketing strategies and improve campaign performance.
Showcase Your Analytical Skills: During the application process, be prepared to discuss your analytical skills in detail. Provide examples of how you've identified trends in data and translated insights into actionable recommendations for marketing.
Highlight Your Curiosity: Demonstrate your natural curiosity about customer behaviour and data findings. Share instances where you've explored the 'why' behind data trends and how that has influenced your work in CRM or marketing analytics.
How to prepare for a job interview at Blue Pelican
✨Showcase Your Analytical Skills
Be prepared to discuss your experience with CRM analytics and how you've used data to drive marketing decisions. Highlight specific projects where you identified trends and generated insights that led to actionable recommendations.
✨Demonstrate Technical Proficiency
Make sure to showcase your SQL and Python skills during the interview. Be ready to explain how you've used these tools in past roles, especially in relation to analysing large datasets and working with cloud warehouses like Redshift.
✨Understand the Company’s Mission
Research Blue Pelican and their consumer champion status. Be ready to discuss how their mission aligns with your values and how you can contribute to their goal of doing good by the consumer through effective customer marketing strategies.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving abilities in a fast-paced environment. Think about how you would approach challenges related to customer behaviour analysis and campaign performance improvement.
