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For Companies At a Glance
- Tasks: Collaborate with clients to enhance marketing effectiveness using data-driven insights.
- Company: Join The Data Gals, a leader in marketing analytics, working with top brands.
- Benefits: Enjoy a hybrid work model and competitive salary ranging from £40,000 to £90,000.
- Why this job: Make an impact in marketing analytics while growing your career in a high-demand field.
- Qualifications: Experience in Marketing Mix Modeling and proficiency in Python, R, SQL, or Excel required.
- Other info: We value diversity and welcome applicants from all backgrounds.
The predicted salary is between 32000 - 72000 £ per year.
Marketing Science Consultants – London (Hybrid)
Salary: £40,000 – £90,000 (DOE)
Employment Type: Full-Time
About the Role:
The Data Gals are partnering with multiple clients in London to expand their marketing science teams. We are seeking experienced Marketing Science Consultants to work with diverse clients, focusing on marketing effectiveness and analytics. This is a client-facing role that requires strong expertise in Marketing Mix Modeling (MMM), regression analysis, Bayesian modeling, and econometric modeling.
Key Responsibilities:
- Collaborate with clients to improve marketing effectiveness and data-driven decision-making.
- Develop and implement Marketing Mix Models (MMM) to analyse and optimise marketing strategies.
- Utilise regression analysis, Bayesian modeling, and econometric modeling techniques to derive actionable insights.
- Work with various tools including Python, R, SQL, and Excel (flexibility in tools is welcomed).
- Present findings and recommendations to clients in an inclusive and accessible manner.
Requirements:
- Proven experience in Marketing Mix Modeling (MMM) is essential.
- Strong knowledge of regression analysis, Bayesian modeling, or econometric modeling.
- Proficiency in Python, R, SQL, or Excel (any combination is welcomed).
- Experience in a client-facing role, with the ability to build strong and inclusive stakeholder relationships.
- Background in agency-side or client-side marketing analytics.
- Full right to work in the UK (sponsorship is not available).
- Ability to work in a hybrid capacity in London.
Why Join Us?
- Opportunity to work with leading brands in the marketing analytics space.
- Career growth opportunities in a high-demand field.
Apply Today!
We welcome applications from individuals of all backgrounds and experiences. If you have the required expertise and are passionate about driving marketing effectiveness through data, we’d love to hear from you! Apply today or send your CV to kat@thedatagals.co.uk
Marketing Science Consultant employer: The Data Gals | by AI Connect
Contact Detail:
The Data Gals | by AI Connect Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Marketing Science Consultant
✨Tip Number 1
Familiarize yourself with the latest trends and tools in marketing science. Being well-versed in Marketing Mix Modeling (MMM) and regression analysis will not only boost your confidence but also demonstrate your expertise during interviews.
✨Tip Number 2
Network with professionals in the marketing analytics field. Attend industry events or webinars to connect with potential colleagues and clients, which can help you gain insights into what companies like ours are looking for in a candidate.
✨Tip Number 3
Prepare to discuss real-world applications of your skills. Be ready to share specific examples of how you've used Python, R, SQL, or Excel to drive marketing effectiveness in previous roles, as this will showcase your practical experience.
✨Tip Number 4
Practice your presentation skills. Since this role involves presenting findings to clients, being able to communicate complex data insights in an accessible way is crucial. Consider doing mock presentations to friends or colleagues for feedback.
We think you need these skills to ace Marketing Science Consultant
Some tips for your application 🫡
Understand the Role: Take the time to thoroughly read the job description for the Marketing Science Consultant position. Make sure you understand the key responsibilities and requirements, especially the importance of Marketing Mix Modeling (MMM) and client-facing experience.
Tailor Your CV: Customize your CV to highlight relevant experience in marketing analytics, particularly focusing on your expertise in MMM, regression analysis, and any tools like Python, R, SQL, or Excel that you are proficient in. Use specific examples to demonstrate your skills.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for marketing effectiveness and data-driven decision-making. Mention how your background aligns with the role and express your enthusiasm for working with diverse clients in London.
Highlight Client-Facing Experience: In your application, emphasize any previous roles where you interacted with clients. Discuss how you built relationships and communicated complex data insights in an accessible manner, as this is crucial for the position.
How to prepare for a job interview at The Data Gals | by AI Connect
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Marketing Mix Modeling (MMM), regression analysis, and other relevant techniques. Highlight specific projects where you've successfully applied these skills, and be ready to explain your thought process.
✨Demonstrate Client-Facing Experience
Since this role is client-facing, share examples of how you've built strong relationships with clients in the past. Discuss how you’ve communicated complex data insights in an accessible way to ensure understanding and buy-in.
✨Familiarize Yourself with Tools
Make sure you are comfortable discussing your proficiency in tools like Python, R, SQL, and Excel. If you have experience with any specific projects using these tools, be ready to elaborate on them during the interview.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving abilities. Think about how you would approach a client's marketing challenge using data-driven insights, and be ready to walk through your reasoning step-by-step.
