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- Tasks: Build predictive models and measure campaign success using data insights.
- Company: Join a leading telecom company shaping the future of digital marketing.
- Benefits: Enjoy remote work flexibility and the chance to innovate in a dynamic team.
- Why this job: Be part of a new team, leverage your skills, and make a real impact on marketing strategies.
- Qualifications: Experience with Python, SQL, and marketing analysis is essential.
- Other info: Opportunity to work with cutting-edge machine learning techniques.
The predicted salary is between 43200 - 72000 £ per year.
Marketing Data Scientist Remote Ads, Attributions, CLV We are working with a large telecoms company who are looking to add a Marketing Data Scientist to their newly formed Digital Marketing team. This person will build attribution and predictive models to look at customer insights. You will also review and measure the success of a campaign. Role: Building Models Measure success of a campaign Paid Media advertising through Ads Python & SQL Machine learning and deployment models Strong marketing knowledge Desired Skills and Experience Marketing Analysis, Google Ads, CLV, Attribution Models
Marketing Data Scientist employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Marketing Data Scientist
✨Tip Number 1
Familiarize yourself with the latest trends in marketing analytics and attribution models. This will not only help you understand the role better but also allow you to speak confidently about your insights during the interview.
✨Tip Number 2
Brush up on your Python and SQL skills, as these are crucial for building models and analyzing data. Consider working on a small project or two that showcases your ability to use these tools in a marketing context.
✨Tip Number 3
Prepare to discuss specific campaigns you've worked on in the past. Be ready to explain how you measured their success and what insights you gained from them, as this will demonstrate your practical experience in marketing analysis.
✨Tip Number 4
Network with professionals in the digital marketing field, especially those who have experience with telecom companies. They can provide valuable insights and may even refer you to opportunities within their organizations.
We think you need these skills to ace Marketing Data Scientist
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly understand the responsibilities of a Marketing Data Scientist. Familiarize yourself with concepts like attribution models, customer lifetime value (CLV), and predictive modeling.
Highlight Relevant Skills: In your CV and cover letter, emphasize your experience with Python, SQL, and machine learning. Mention any specific projects where you built models or analyzed marketing data.
Showcase Marketing Knowledge: Demonstrate your understanding of marketing principles, especially in relation to paid media advertising and campaign success measurement. Use examples from your past work to illustrate your expertise.
Tailor Your Application: Customize your application materials to align with the job description. Use keywords from the listing, such as 'Google Ads' and 'Attribution Models', to ensure your application stands out.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and SQL in detail. Highlight specific projects where you've built models or analyzed data, especially in the context of marketing.
✨Demonstrate Marketing Knowledge
Make sure to brush up on key marketing concepts like customer lifetime value (CLV) and attribution models. Be ready to explain how these concepts apply to your previous work and how they can benefit the telecom company.
✨Prepare for Case Studies
Expect to tackle case studies or hypothetical scenarios during the interview. Practice analyzing campaign success metrics and be ready to suggest improvements based on your findings.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's digital marketing strategies and how they measure campaign success. This shows your genuine interest in the role and helps you understand their expectations better.
