Contribute to one major or multiple client projects across our suite of MMM/Data science offerings
Clean and prepare data from multiple sources using Python, R, SQL, Excel, or other tools.
Conduct analyses related to consumer behaviour, market trends, and campaign performance.
Build, maintain, and apply statistical and predictive models, including regression, econometrics, Bayesian methods, and Marketing Mix Modelling (MMM).
Develop dashboards, charts, and visualizations to communicate insights effectively to clients and internal teams.
Assist in developing marketing strategies and media optimization plans based on model insights.
Collaborate with teams to produce client deliverables, ensuring accuracy, quality, and timely delivery.
Participate in client meetings and calls under supervision, helping translate analytical outputs into actionable business recommendations and narratives.
Collaborate with seniors and managers to define analytical approaches and methodologies
Support informed decision making by presenting and explaining findings in client delivery meetings and internal workshops
Share best practices within the team and contribute to knowledge-sharing initiatives.
Take ownership of your professional development, pursuing certifications and training in analytics, modelling, and programming.
Actively participate in office meetings, training sessions, and team initiatives.
Champion and role-model our core values: Curiosity, Creativity, Excellence, Transmission, Pleasure.

Requirements

1–3 years of professional experience in analytics, data science, or marketing effectiveness, including internships or graduate placements.
Proven hands-on experience with Marketing Mix Modelling (MMM) and related marketing effectiveness methodologies.
Bachelor’s or Master’s degree (or equivalent) in Statistics, Econometrics, Data Science, Economics, Applied Mathematics, Business Analytics, Marketing, or a related analytical field.
Strong technical proficiency in Python, R, SQL, or similar analytics tools; experience with Databricks, Azure, or other cloud/data platforms is a plus.
Experience or willingness to learn visualisation tools such as PowerBi and Tableau
Experience building and maintaining statistical or predictive models to forecast consumer behaviour, campaign performance, and key business metrics
Ability to handle and optimize large datasets, ensuring high-quality analyses and actionable insights.
Strong working knowledge of Microsoft Excel and PowerPoint.

Benefits

Salary £40,000-£55,000 + Bonus 10% + Corporate bonus
Enter into our generous Bonus scheme, reflecting individual performance and corporate, reducing CO2
Regular events and seminars to connect with colleagues
Modern office space in a central London location
Flexible hybrid working policy (2 days a week in office + 20 days’ work from anywhere, remotely)
25 days annual leave + bank holidays, plus an additional 3 days for tenure
Private healthcare, life insurance, and wellbeing support
Group pension scheme
Opportunities for international mobility and career development

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonRSQLMarketing Mix Modelling (MMM)statistical modelspredictive modelsregressioneconometricsBayesian methodsdata cleaning

Soft Skills

collaborationcommunicationcuriositycreativityexcellencetransmissionpleasureownershipanalytical thinkingproblem-solving