> Markdown version of [/jobs/ext/3975375-fbs-mexico-decision-scientist-mmm](https://www.wearedevelopers.com/jobs/ext/3975375-fbs-mexico-decision-scientist-mmm). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # FBS (Mexico) - Decision Scientist (MMM) - **Company:** Farmers Insurance - **Location:** United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Big Data, Python (Programming Language), Machine Learning, Marketing Information Systems - **Published:** October 27, 2026 - **Apply:** https://jobs.farmersinsurance.com/talentcommunity/apply/1375891857/?locale=en_US ## About the Role Bachelor's degree in a technical field., * Experience with MMM (Marketing Mix Models) * At least 3 years of experience in analytics and/or Data Science, preferably in marketing and/or MMM * Knowledge of statistics and Machine Learning * Experience working with large and complex datasets * Working knowledge of R or Python * Fluency in English ## Description We are seeking a Decision Scientist with experience in Marketing Mix Modeling (MMM) and advanced analytics to join our team. This role will play a key part in measuring marketing effectiveness, forecasting business performance, and generating actionable insights that support strategic decision-making and optimize marketing spend. Team Function: The Marketing Data Science and Measurement team supports the media team in optimizing media investment. It develops and maintains measurement and attribution models to assist in decision making and budget allocation. Role Description: This role will be responsible for: * Maintaining and improving our in-house Marketing Mix Model (MMM) * Presenting results from the MMM leadership and stakeholders to inform channel allocation and budget planning. * Creating forecasts of expected future sales to allow for adequate preparation and optimal investment. * Developing other forms of marketing measurement to provide a full picture of marketing effectiveness. The ideal candidate will have deep knowledge of statistical and machine learning techniques and will be comfortable interpreting results of analyses to stakeholders across a wide range of seniority, from entry-level to C-suite. They will be able to clearly communicate actionable insights that will improve marketing efficiency.