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- Tasks: Lead data activities for Marketing Mix Modelling, including analysis and model validation.
- Company: Join a leading multinational FMCG brand making waves in the market.
- Benefits: Enjoy hybrid working, long-term contract options, and a dynamic work environment.
- Why this job: Be part of a project shaping marketing strategies over the next few years with real impact.
- Qualifications: Advanced degree in Data Science or related field; strong Python and SQL skills required.
- Other info: Opportunity for long-term career growth and development in a collaborative team.
The predicted salary is between 48000 - 72000 £ per year.
Location: London (Hybrid Working)
Duration: Minimum 12 month contract + long term extensions - Project scope scheduled for the next 3/4 years.
Start Date: ASAP
We have an excellent opportunity for a Senior Marketing Data Scientist/MMM Specialist to join a multinational FMCG brand in London. Hybrid working, initial 12 month contract + opportunity to extend long-term & start date ASAP.
Role Summary:
Lead data activities including extraction, transformation, analysis, and validation to support Marketing Mix Modelling (MMM). Build, enhance, and validate models to analyze KPIs and guide budget optimization and scenario planning.
Key Responsibilities:
- Extract, manipulate, and analyze datasets to prepare for modelling (Excel, SQL, Python, Pandas).
- Build and refine base models with clear variable rationale and KPI linkage.
- Create ROI workbooks, response curves, and optimization charts.
- Run scenarios for budget allocation and client objectives.
- Validate models for accuracy, suggest and test improvements.
Required Skills & Experience:
- Proven experience with MMM development and implementation.
- Strong Python skills; familiarity with R for MMM.
- Expertise in regression modeling, statistical and ML techniques.
- Experience with probabilistic programming, Bayesian methods, PyMC and MCMC.
- Proficient in SQL and/or Spark for large-scale data mining.
- Solid understanding of statistical foundations and mathematical modelling.
- Familiarity with cloud-based frameworks; Azure preferred.
- Advanced degree (MS/PhD) in Data Science, Computer Science, Statistics, Applied Math, or related field.
Strong Points:
- Deep technical specialization in optimization, simulation, and applied math.
- Ability to translate complex models into actionable business insights.
Contact Detail:
Placed Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Marketing Data Scientist (London Area)
✨Tip Number 1
Network with professionals in the marketing data science field, especially those who have experience with Marketing Mix Modelling. Attend industry events or webinars to connect with potential colleagues and learn about the latest trends and techniques.
✨Tip Number 2
Showcase your technical skills by working on relevant projects or case studies that demonstrate your expertise in Python, SQL, and statistical modelling. Having a portfolio of your work can set you apart from other candidates.
✨Tip Number 3
Familiarise yourself with the specific tools and frameworks mentioned in the job description, such as Azure and Bayesian methods. Being able to discuss these technologies confidently during interviews will show your commitment and readiness for the role.
✨Tip Number 4
Prepare to discuss how you've translated complex data models into actionable business insights in previous roles. This will demonstrate your ability to not only analyse data but also to apply it effectively in a marketing context.
We think you need these skills to ace Senior Marketing Data Scientist (London Area)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in Marketing Mix Modelling (MMM) and showcases your strong Python skills. Include specific projects where you've used regression modelling or statistical techniques.
Craft a Compelling Cover Letter: In your cover letter, explain why you're passionate about data science in marketing. Mention your familiarity with tools like SQL and your experience with cloud-based frameworks, particularly Azure, to demonstrate your fit for the role.
Showcase Your Technical Skills: When detailing your experience, emphasise your expertise in data extraction, transformation, and analysis. Provide examples of how you've built and validated models, and discuss any experience with probabilistic programming or Bayesian methods.
Highlight Business Impact: Illustrate how your work has led to actionable business insights. Use metrics or specific outcomes from previous roles to show how your data-driven decisions have optimised budgets or improved marketing strategies.
How to prepare for a job interview at Placed
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, SQL, and any other relevant tools. Highlight specific projects where you've successfully implemented Marketing Mix Modelling (MMM) and how your technical skills contributed to the outcomes.
✨Demonstrate Your Analytical Thinking
During the interview, be ready to explain your thought process when analysing data. Use examples to illustrate how you approach problem-solving, especially in relation to regression modelling and statistical techniques.
✨Prepare for Scenario-Based Questions
Expect questions that ask you to run through scenarios related to budget allocation or KPI analysis. Practise articulating your approach to these scenarios, focusing on how you would validate models and suggest improvements.
✨Communicate Complex Ideas Simply
Since the role involves translating complex models into actionable insights, practise explaining your work in a way that non-technical stakeholders can understand. This will demonstrate your ability to bridge the gap between data science and business needs.
