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- Tasks: Lead marketing data projects, refine testing frameworks, and extract insights from complex data sets.
- Company: Join a dynamic team focused on innovative marketing analytics in the eCommerce space.
- Benefits: Enjoy flexible working options, competitive salary, and opportunities for professional growth.
- Why this job: Make an impact by translating data into strategies that drive marketing success and enhance customer experiences.
- Qualifications: 4-5 years in data science, strong skills in Python and SQL, and experience with MMM and A/B testing.
- Other info: Ideal for those passionate about data-driven marketing and eager to collaborate across teams.
The predicted salary is between 36000 - 60000 £ per year.
Role and Responsibilities:
- Leading and finalising the Marketing Mix Modelling (MMM) framework.
- Refining and taking ownership of an A/B testing framework, ensuring rigorous experiment design and causal inference methodology.
- Automating marketing analytics pipelines, especially around incremental measurement and experimentation.
- Collaborating cross-functionally to support campaign evaluation across key platforms (e.g., Meta, Google).
- Working hands-on with complex, incomplete data sets to extract meaningful insights on campaign performance.
- Supporting ongoing projects in customer life cycle modelling and Lifetime Value (LTV) analysis.
- Contributing to strategic decision-making by translating data into actionable insights for marketing and leadership teams.
- Navigating the intricacies of working across third-party clients to ensure adaptability and broad marketing perspective.
Requirements:
- 4-5 years of experience in data science, ideally in eCommerce or marketing analytics.
- Proven experience working with either Robyn or Meridian.
- Strong skills in Python, SQL, and working with large-scale data (Databricks, PySpark).
- Proven experience with MMM, A/B testing, and causal inference.
- Comfortable with experimentation design, time series analysis, and working with imperfect data.
- Bonus: Experience with R and dashboarding tools.
- Clear communicator with the ability to translate data into strategy.
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
Familiarise yourself with the latest trends in Marketing Mix Modelling (MMM) and A/B testing frameworks. Being able to discuss recent advancements or case studies during your interview can demonstrate your passion and expertise in the field.
✨Tip Number 2
Brush up on your Python and SQL skills, especially in relation to data manipulation and analysis. Consider working on personal projects or contributing to open-source projects that showcase your ability to handle large-scale data sets.
✨Tip Number 3
Network with professionals in the marketing analytics space, particularly those who have experience with tools like Robyn or Meridian. Engaging in relevant online communities or attending industry events can provide valuable insights and connections.
✨Tip Number 4
Prepare to discuss how you've translated complex data into actionable insights in previous roles. Think of specific examples where your analysis led to strategic decisions, as this will highlight your ability to contribute to our marketing and leadership teams.
We think you need these skills to ace Marketing Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly in eCommerce or marketing analytics. Emphasise your skills in Python, SQL, and any experience with tools like Robyn or Meridian.
Craft a Compelling Cover Letter: In your cover letter, explain how your background aligns with the role's responsibilities. Discuss your experience with Marketing Mix Modelling and A/B testing, and provide examples of how you've translated data into actionable insights.
Showcase Your Technical Skills: Include specific projects or achievements that demonstrate your proficiency in handling large-scale data and your ability to work with complex datasets. Mention any experience with Databricks, PySpark, or dashboarding tools if applicable.
Prepare for Potential Questions: Anticipate questions related to your experience with experimentation design and causal inference methodology. Be ready to discuss how you've approached challenges in previous roles and the impact of your work on marketing strategies.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Skills
Make sure to highlight your experience with Python, SQL, and any tools like Robyn or Meridian. Be prepared to discuss specific projects where you've used these skills, especially in the context of marketing analytics.
✨Demonstrate Your Understanding of MMM and A/B Testing
Be ready to explain your approach to Marketing Mix Modelling and A/B testing. Discuss how you ensure rigorous experiment design and causal inference methodology, as this will be crucial for the role.
✨Prepare for Data Challenges
Since the role involves working with complex and incomplete data sets, think of examples where you've successfully navigated similar challenges. Share how you extracted meaningful insights despite data imperfections.
✨Communicate Clearly and Effectively
As a clear communicator, practice translating complex data insights into actionable strategies. Prepare to discuss how you've done this in past roles, particularly when collaborating with cross-functional teams.
