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For Companies At a Glance
- Tasks: Lead data analysis and client presentations to shape marketing strategies.
- Company: Join a global agency focused on innovative marketing solutions.
- Benefits: Enjoy a competitive salary, mentorship opportunities, and a collaborative team environment.
- Why this job: Make an impact with data-driven insights while developing your management skills.
- Qualifications: Bachelor's degree in a quantitative field and 4-5 years of relevant experience required.
- Other info: Diversity and inclusion are core values; all qualified applicants are encouraged to apply.
The predicted salary is between 40000 - 84000 £ per year.
Ref: BBBH4515
Location: City of London, London
Salary: £50,000 – £60,000 per annum
Type: Permanent
Job Description
The Role:
An exciting opportunity for a Marketing Mixed Modelling technical expert working for a global agency. You will work closely with the Analytics Directors to manage resources, implement process improvements and provide mentorship within a tight-knit account team consisting of analysts, media planners and strategists as they work to analyse data and deliver valuable and relevant insights. Through data-driven insights, you will have the opportunity to shape the strategic direction of a client’s marketing strategy.
Responsibilities:
Client Relationship Management
- Client Presentation: Present findings/insights as well as methodology/data approaches reliably to clients through a variety of different presentation opportunities.
Team Operations
- Collaboration: Connect across planning, investment, and technology teams to ensure holistic understanding of data.
- Management: Start your management career by having Associate, Sr. Associate and Associate Managers reporting into you and managing their workload and career development.
Audience Discovery & Strategy
- Data Analysis: Become more seasoned in audience definition, creation and strategy using multiple data sources.
- Data Analysis Management: Manage your team to organise and analyse data and facilitate insight generation for which you will be responsible.
- Data Sources: Employ solid understanding of Audience data sources and how to best leverage them for each type of analysis.
Measurement & Reporting
- Measurement: Develop breadth of knowledge measurement strategy, frameworks and technology.
- Benchmarks & Goals: Set benchmarks and targets based on historical campaign data.
- Reporting & Optimization: Oversee and QA the development of reports and directing optimisation initiatives.
- Insights: Hone the ability to know what an insight is, and developing them for the campaigns.
Data Strategy & Technology
- Data Technology Utilisation: Manage your team to oversee automation and improve processes for efficiencies.
- Data Management: Be accountable for the maintenance and QA of data systems and processes used for reporting and on-going data analysis.
- Data Visualization: Develop advanced dashboards in visualization tools such as Tableau/QlikView/Looker.
- Ad Operations: Apply advanced understanding of Ad Operations and QA procedures.
- AdTech/MarTech: Evaluate and compare data, ad and MarTech vendors.
Qualifications & Expertise Required:
- Bachelor’s degree in Statistics, Mathematics, Economics, Engineering, Information Management, Social Sciences or Business/Marketing related fields (advanced degree – MBA/MS – is preferred).
- 4-5 years of experience in a quantitative data-driven field.
- A passion for digital marketing, research and analytics.
- Excellent communication and presentation skills.
- Ability to work well with others and work in cross-functional teams.
- Ability to manage and prioritise a number of concurrent tasks.
- Ability to clearly explain complex technical ideas to multiple audiences both verbally and in writing.
- Comprehensive knowledge of ad technologies and research techniques (how they work, and how to troubleshoot).
- Ability to move beyond descriptive analytics and employ more sophisticated techniques (predictive & prescriptive analytics).
- Ability to set individual goals for analysts and measuring individual success/performance.
- Experience/familiarity in SAS, SPSS, R or other advanced analytics software packages.
- Experience/familiarity in ad-serving and web analytics tools (Google DFA, Atlas, Google Analytics, Omniture, etc.).
- Experience/familiarity with concepts of database design and SQL.
- Experience/familiarity with syndicated research sources/tools (Gfk, MRI, Simmons, Scarborough, IMS, Nielsen, comScore).
- Experience/familiarity with digital ad effectiveness research.
- Proficiency with Microsoft Excel and PowerPoint & a Data visualisation tool (Tableau).
- Familiarity with web technologies including HTML and Javascript.
Diversity, equity and inclusion are at the heart of what we value as an organisation. Boston Hale is an equal opportunities employer, and all qualified applicants will receive consideration for employment without regard to race, religion, sex, sexual orientation, age, disability or any other status protected by law.
Sophie Liddle
Consultant
020 7048 6970
#J-18808-Ljbffr
Marketing Mix Modelling Data Scientist employer: Boston Hale
Contact Detail:
Boston Hale Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Marketing Mix Modelling Data Scientist
✨Tip Number 1
Familiarize yourself with the latest trends in marketing mix modeling and data analytics. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the field of data science and marketing. Attend industry events or webinars where you can meet people who work in similar roles, as they might provide insights or even referrals for job openings.
✨Tip Number 3
Brush up on your presentation skills. Since the role involves client presentations, being able to convey complex data insights clearly and confidently will set you apart from other candidates.
✨Tip Number 4
Gain hands-on experience with tools like Tableau, SAS, or R if you haven't already. Having practical knowledge of these technologies will demonstrate your capability to manage data analysis and visualization effectively.
We think you need these skills to ace Marketing Mix Modelling Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data analysis, marketing, and client relationship management. Use specific examples that demonstrate your ability to work with data-driven insights and your familiarity with tools like SAS, SPSS, or R.
Craft a Compelling Cover Letter: In your cover letter, express your passion for digital marketing and analytics. Mention how your skills align with the responsibilities outlined in the job description, particularly in managing teams and presenting insights to clients.
Showcase Communication Skills: Since excellent communication is key for this role, provide examples in your application of how you've successfully communicated complex ideas to different audiences. This could be through presentations, reports, or team collaborations.
Highlight Technical Proficiency: Clearly outline your experience with data visualization tools like Tableau, as well as your proficiency in SQL and web analytics tools. Mention any specific projects where you utilized these skills to drive results.
How to prepare for a job interview at Boston Hale
✨Showcase Your Analytical Skills
Be prepared to discuss your experience with data analysis and how you've used it to drive marketing strategies. Highlight specific projects where you applied advanced analytics techniques, such as predictive or prescriptive analytics.
✨Communicate Complex Ideas Clearly
Since the role requires explaining complex technical concepts to various audiences, practice articulating your thoughts clearly and concisely. Use examples from your past experiences to demonstrate your ability to simplify intricate ideas.
✨Demonstrate Team Collaboration
Emphasize your experience working in cross-functional teams. Share examples of how you've collaborated with analysts, media planners, and strategists to achieve common goals, showcasing your teamwork and leadership skills.
✨Prepare for Client Presentations
Since client relationship management is key, practice presenting your findings and insights. Be ready to discuss how you would approach a client presentation, including how you would tailor your message to different stakeholders.
