Marketing Data Lead Carbon

Bayer•St. Louis, MO

4d•$160,000 - $190,000•Hybrid

About The Position

The Marketing Data Lead Carbon will establish and implement agronomic data quality control and quality assurance rules for data collection. The role verifies field-practice evidence, boundaries, and payment eligibility; ensures grower data compliance; and plans data modeling for carbon assets. It also implements automation to improve processes, uses data and analytics to inform marketing initiatives, and trains internal stakeholders on digital analytics best practices. The position identifies data trends, opportunities, and issues; leads a cross-functional team evaluating data quality for carbon modeling; and establishes data correction rules and processes to ensure data meets registry requirements. Telecommuting is permitted within reasonable commuting distance of St. Louis, Missouri, up to two days per week. The salary range is $160,000 to $190,000. Additional compensation may include a bonus or commission, if relevant. Benefits include health care, vision, dental, retirement, paid time off, and sick leave. Salary may vary based on location, market data, skills, relevant experience, degrees, certifications, and other factors.

Requirements

Master’s degree in Marketing Analytics, Data Science, Operations Research, or a closely related field.
Six years of experience manipulating large datasets using computer applications to analyze, test, validate, and report data and ensure accuracy and efficiency of outputs.
Six years of experience using statistical query languages, including SAS, SQL, Python, and/or R, to store and transform data from multiple sources, including third-party data and/or large-scale databases, for delivery to end users.
Six years of experience using and leveraging data visualization and automation tools, including Tableau and/or PowerBI.
Six years of experience developing business analytics reporting and dashboards to understand data trends, outliers, and patterns.
Six years of experience using statistical methodologies, including sample sizing, decision tree, and/or linear regression, to translate analytical results into actionable insights and recommendations.

Responsibilities

Establish and implement agronomic data quality control and quality assurance rules for data collection.
Verify field-practice evidence, boundaries, and payment eligibility.
Ensure grower data compliance.
Plan data modeling for carbon assets.
Implement automation techniques to improve processes.
Use data and analytics to inform marketing initiatives.
Train internal stakeholders on digital analytics best practices.
Identify data trends, opportunities, and issues.
Lead a cross-functional team evaluating data quality for carbon modeling.
Establish data correction rules and ensure data meets registry requirements through correction processes.