Data Scientist - Marketing Modelling (MMM)

About Us:

Founded in 2003, BIP is a multinational consulting company that develops projects for the world’s leading companies and organizations. We combine a strategic approach with a “make it happen” mindset to support organizations on their transformation journey.

We are one of the fastest-growing consulting firms globally, with more than 6,000 people across 22 offices in 15 countries.

Within BIP, our xTech Center of Competence brings together experts in data, cloud, and AI to design and deliver next-generation analytics solutions. We work at the intersection of business and technology, translating complex data into actionable insights.

We strive for excellence in everything we do, guided by a collaborative, innovative, and entrepreneurial spirit. We are here to dare.

Job Description:

We are looking for a Data Scientist specialized in Marketing Modelling (MMM) to join our growing analytics team.

In this role, you will design, build, and deploy advanced econometric and statistical models to support marketing investment decisions for leading clients, particularly in CPG / consumer goods environments.

You will play a key role in translating complex modelling outputs into clear, actionable recommendations that drive measurable business impact.

Key Responsibilities:

• Design, build, validate, and maintain Marketing Mix Models (MMM), including adstock/carryover effects, saturation curves, and channel attribution
• Translate modelling outputs into budget allocation, ROI insights, and scenario planning recommendations
• Calibrate, validate, and continuously improve model performance and robustness
• Develop and implement optimization models to support efficient media investment allocation
• Work closely with business stakeholders (marketing, media, finance) to ensure model relevance and adoption
• Present complex analytical findings in a clear, structured, and business-oriented way

Required Skills & Experience:

• 3–5 years of experience in data science, marketing science, or advanced analytics
• Strong background in statistical modelling (regression, time-series, Bayesian methods, causal inference)
• Proficiency in Python and SQL
• Hands-on experience with Databricks (Spark/PySpark, Delta Lake, MLflow)
• Experience with operations research / optimization models in Python
• Experience working with CPG / consumer goods data
• Solid understanding of marketing dynamics in a CPG context (media channels, promotions, trade activity, and sales drivers)

Nice to Have

• Direct experience building Marketing Mix Models (MMM) (adstock, saturation, attribution), using tools such as PyMC or similar
• Familiarity with media KPIs and digital attribution frameworks
• Experience with experimentation, incrementality measurement, and causal impact analysis

Next Steps:

Once we receive your CV, we will take the time to review it thoroughly. If there is a match with this or other open positions within the Group, we will contact you to start getting to know each other better.