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For Companies At a Glance
- Tasks: Analyse data to enhance marketing strategies and drive business insights.
- Company: Join a leading sports and gaming company at the forefront of innovation.
- Benefits: Enjoy a competitive salary, bonus, and hybrid work options.
- Why this job: Be part of a dynamic team shaping the future of marketing effectiveness in gaming.
- Qualifications: Data-driven mindset with a passion for econometrics and marketing analytics.
- Other info: Work in vibrant Soho, London, with a focus on advanced analytics and machine learning.
The predicted salary is between 36000 - 60000 £ per year.
MBN has a rare client-side opportunity in the econometrics space to join a leading sports and gaming company. Are you a data-driven problem solver with a passion for marketing effectiveness? Join our fast-growing Marketing & Business Insights team and play a key role in shaping our in-house Econometrics/MMM capability. This is a unique opportunity to work at the intersection of gaming and sports, leveraging customer-level data, machine learning models, and advanced analytics to drive strategic decision-making.
Econometrician employer: MBN Solutions
Contact Detail:
MBN Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Econometrician
✨Tip Number 1
Familiarise yourself with the latest trends in econometrics and marketing effectiveness. Being able to discuss recent developments or case studies during your interview can demonstrate your passion and knowledge in the field.
✨Tip Number 2
Network with professionals in the gaming and sports industries. Attend relevant events or webinars where you can meet people who work in these sectors, as they might provide insights or even referrals that could help you land the job.
✨Tip Number 3
Brush up on your data analysis skills, particularly with tools and software commonly used in econometrics. Being proficient in programming languages like R or Python, as well as data visualisation tools, can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss how you would approach real-world problems related to marketing effectiveness. Think of examples where you can showcase your problem-solving skills and how you would apply econometric models to improve business outcomes.
We think you need these skills to ace Econometrician
Some tips for your application 🫡
Understand the Role: Familiarise yourself with the specific responsibilities of an Econometrician in the marketing effectiveness space. Highlight your experience with data-driven problem solving and any relevant projects you've worked on.
Tailor Your CV: Make sure your CV reflects your skills in econometrics, machine learning, and advanced analytics. Use keywords from the job description to ensure your application stands out to recruiters.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for marketing effectiveness and your understanding of the gaming and sports industry. Mention how your background aligns with the company's goals and how you can contribute to their Marketing & Business Insights team.
Highlight Relevant Experience: In your application, emphasise any previous roles or projects where you used customer-level data and analytics to drive decision-making. Provide specific examples that demonstrate your impact in similar positions.
How to prepare for a job interview at MBN Solutions
✨Showcase Your Analytical Skills
As an Econometrician, your ability to analyse data is crucial. Be prepared to discuss specific projects where you've used data-driven insights to solve problems or improve marketing effectiveness. Highlight any experience with machine learning models and advanced analytics.
✨Understand the Industry
Familiarise yourself with the sports and gaming industry, especially how econometrics applies to marketing strategies within this sector. Being able to discuss current trends and challenges will demonstrate your genuine interest and knowledge.
✨Prepare for Technical Questions
Expect technical questions related to econometrics and statistical methods. Brush up on key concepts and be ready to explain your thought process in tackling complex data problems. This will show your depth of understanding and problem-solving abilities.
✨Demonstrate Team Collaboration
Since the role involves working within a team, be ready to share examples of how you've successfully collaborated with others in past roles. Emphasise your communication skills and how you can contribute to a positive team dynamic.
