Do you love using data and causal methods to shape real marketing decisions and budgets?

As a Lead Data Scientist – Marketing Measurement at General Mills, you’ll use advanced statistics, econometrics, and machine learning to measure what truly drives growth and to optimize how we invest our marketing dollars across channels.

You will partner closely with marketing, and media teams to build and evolve our Marketing Mix Models (MMM) and related measurement frameworks—translating complex insights into clear recommendations that influence brand and portfolio strategy.

To make the food people love, we need to make sure we feed our decision makers the right data and solutions at the right time, every time.

You will play a critical role in that mission. KEY ACCOUNTABILITIES Measurement & Modeling Develop, validate, and maintain robust Marketing Mix Models (MMM) and related marketing effectiveness models to quantify the impact of media and non-media drivers on business outcomes.

Design and implement causal measurement strategies, including approaches such as Difference-in-Differences, Regression Discontinuity, and causal ML, to estimate incremental impact.

Conduct in-depth statistical and econometric analysis to measure marketing effectiveness, forecast future performance, and inform investment and scenario planning.

Experimentation & Optimization Design, recommend, and execute statistically rigorous A/B and multivariate tests (“Test & Measurement”) for marketing campaigns.

Recommend optimal budget allocation and channel mix strategies based on model outputs and experiment results.

Collaborate with machine learning engineering and data engineering to ensure models are production-ready, monitored, and continuously improved.

Stakeholder Influence Translate complex model insights into clear, actionable recommendations for diverse stakeholders, including marketing, media, and senior leadership.

Partner with business and product owners to frame ambiguous problems, shape learning agendas, and prioritize high-impact measurement initiatives.

Provide thought leadership on marketing effectiveness and help shape how General Mills measures and learns from its marketing investments.

Technical & Team Leadership Provide data science leadership within a product/team context, including roadmap input, technical standards, and best practices.

Coach and mentor junior data scientists, providing guidance on solution design, methods, and domain-specific techniques.

Contribute to the broader data science community at General Mills through knowledge sharing, documentation, and collaboration.

MINIMUM QUALIFICATIONS:

Education: &

Experience: One of the following: Graduate degree (Master’s or PhD) in Mathematics, Statistics, Data Science, Operations Research, Econometrics, Applied Economics, Computer Science, or a related quantitative field with 5+ years of professional experience as a hands-on coding Data Scientist, or Bachelor’s degree in a related quantitative field with 7+ years of professional experience as a hands-on coding Data Scientist.

Substantial, real-world experience with Marketing Mix Modeling: Hands-on responsibility for building, refining, or maintaining MMM (or very closely related marketing effectiveness models) that have been used to guide budget allocation or channel strategy.

Technical Expertise Expert-level programming in Python and SQL, including demonstrated experience working with large, complex datasets and writing advanced SQL queries.

Deep understanding of causal modeling principles (e.g., DAG design, assumptions and falsification, Difference-in-Differences, Regression Discontinuity) and regression modeling (e.g., panel data, time series, regularized regression such as ridge).

Experience: with Bayesian modeling (e.g., PyMC) and MMM / marketing effectiveness frameworks (e.g., PyMC-based MMM, Meridian, Robyn, or similar).

Familiarity with modern machine learning methods, such as Gradient Boosting / XGBoost, and how to integrate these into broader modeling solutions.

Experience: working in cloud-based data and AI environments.

Business & Communication Proven track record of influencing marketing and business decisions using MMM and other measurement approaches, including surfacing insights and tradeoffs to senior stakeholders.

Ability to translate complex analytical and statistical concepts into clear narratives, visualizations, and recommendations for non-technical audiences.

Highly curious, adaptable, and comfortable working independently on complex, ambiguous problems, with a strong bias for action and effective prioritization and time management.

Preferred Qualifications:

Experience: in marketing analytics agencies, consulting firms, or in-house media/marketing effectiveness teams.

Experience: with MLOps practices for analytical models (versioning, monitoring, performance tracking) is a plus. ADDITIONAL CONSIDERATIONS The preferred location for this role is Minneapolis, MN; however remote work-at-home applications within the United States will be considered.

Relocation or international remote working arrangements (outside of the US) will not be considered.

Applicants for this position must be currently authorized to work in the United States on a full-time basis.

General Mills will not sponsor applicants for this position for work visas

Salary: Range The salary range for this position is $126700.00 - $211200.00 / Annually.

At General Mills we strive for each employee's pay at any point in their career to reflect their experiences performance and skills for their current role.

The salary range for this role represents the numerous factors considered in the hiring decisions including, but not limited to, educations, skills, work experience, certifications, etc.

As such, pay for the successful candidate(s) could fall anywhere within the stated range.

Beyond base salary, General Mills offers a competitive Total Rewards package focusing on your overall well-being.

We are proud to offer a foundation of health benefits, retirement and financial wellbeing, time off programs, wellbeing support and perks.

Benefits may vary by role, country, region, union status, and other employment status factors.

You may also be eligible to participate in an annual incentive program.

An incentive award, if any, depends on various factors, including, individual and organizational performance.

Reasonable Accommodation Request If you need to request an accommodation during the application or hiring process, please fill out our online accommodations request form by following this link: Accommodations Request.

Do you love using data and causal methods to shape real marketing decisions and budgets?

As a Lead Data Scientist – Marketing Measurement at General Mills, you’ll use advanced statistics, econometrics, and machine learning to measure what truly drives growth and to optimize how we invest our marketing dollars across channels.

You will partner closely with marketing, and media teams to build and evolve our Marketing Mix Models (MMM) and related measurement frameworks—translating complex insights into clear recommendations that influence brand and portfolio strategy.

To make the food people love, we need to make sure we feed our decision makers the right data and solutions at the right time, every time.

You will play a critical role in that mission. KEY ACCOUNTABILITIES Measurement & Modeling Develop, validate, and maintain robust Marketing Mix Models (MMM) and related marketing effectiveness models to quantify the impact of media and non-media drivers on business outcomes.

Design and implement causal measurement strategies, including approaches such as Difference-in-Differences, Regression Discontinuity, and causal ML, to estimate incremental impact.

Conduct in-depth statistical and econometric analysis to measure marketing effectiveness, forecast future performance, and inform investment and scenario planning.

Experimentation & Optimization Design, recommend, and execute statistically rigorous A/B and multivariate tests (“Test & Measurement”) for marketing campaigns.

Recommend optimal budget allocation and channel mix strategies based on model outputs and experiment results.

Collaborate with machine learning engineering and data engineering to ensure models are production-ready, monitored, and continuously improved.

Stakeholder Influence Translate complex model insights into clear, actionable recommendations for diverse stakeholders, including marketing, media, and senior leadership.

Partner with business and product owners to frame ambiguous problems, shape learning agendas, and prioritize high-impact measurement initiatives.

Provide thought leadership on marketing effectiveness and help shape how General Mills measures and learns from its marketing investments.

Technical & Team Leadership Provide data science leadership within a product/team context, including roadmap input, technical standards, and best practices.

Coach and mentor junior data scientists, providing guidance on solution design, methods, and domain-specific techniques.

Contribute to the broader data science community at General Mills through knowledge sharing, documentation, and collaboration.

MINIMUM QUALIFICATIONS:

Education: &

Experience: One of the following: Graduate degree (Master’s or PhD) in Mathematics, Statistics, Data Science, Operations Research, Econometrics, Applied Economics, Computer Science, or a related quantitative field with 5+ years of professional experience as a hands-on coding Data Scientist, or Bachelor’s degree in a related quantitative field with 7+ years of professional experience as a hands-on coding Data Scientist.

Substantial, real-world experience with Marketing Mix Modeling: Hands-on responsibility for building, refining, or maintaining MMM (or very closely related marketing effectiveness models) that have been used to guide budget allocation or channel strategy.

Technical Expertise Expert-level programming in Python and SQL, including demonstrated experience working with large, complex datasets and writing advanced SQL queries.

Deep understanding of causal modeling principles (e.g., DAG design, assumptions and falsification, Difference-in-Differences, Regression Discontinuity) and regression modeling (e.g., panel data, time series, regularized regression such as ridge).

Experience: with Bayesian modeling (e.g., PyMC) and MMM / marketing effectiveness frameworks (e.g., PyMC-based MMM, Meridian, Robyn, or similar).

Familiarity with modern machine learning methods, such as Gradient Boosting / XGBoost, and how to integrate these into broader modeling solutions.

Experience: working in cloud-based data and AI environments.

Business & Communication Proven track record of influencing marketing and business decisions using MMM and other measurement approaches, including surfacing insights and tradeoffs to senior stakeholders.

Ability to translate complex analytical and statistical concepts into clear narratives, visualizations, and recommendations for non-technical audiences.

Highly curious, adaptable, and comfortable working independently on complex, ambiguous problems, with a strong bias for action and effective prioritization and time management.

Preferred Qualifications:

Experience: in marketing analytics agencies, consulting firms, or in-house media/marketing effectiveness teams.

Experience: with MLOps practices for analytical models (versioning, monitoring, performance tracking) is a plus. ADDITIONAL CONSIDERATIONS The preferred location for this role is Minneapolis, MN; however remote work-at-home applications within the United States will be considered.

Relocation or international remote working arrangements (outside of the US) will not be considered.

Applicants for this position must be currently authorized to work in the United States on a full-time basis.

General Mills will not sponsor applicants for this position for work visas