Senior Scientist - Experimentation

About the Role

Key Responsibilities

• Work on a diverse, cross-functional team (technical and non-technical) to implement high-impact, data-driven solutions addressing business challenges in vehicle brand marketing, ensuring project deliverables meet business needs and timelines.
• Bring strong contextual business knowledge and domain expertise in advertising, paid media, and digital marketing, including understanding of key metrics such as CTR, CPC, CPM, and conversion rates, as well as familiarity with industry measurement platforms.
• Develop and apply advanced modeling techniques, including causal inference methods (e.g., difference-in-differences, synthetic control), machine learning, and other statistical approaches to optimize media strategies, understand incremental impact, and improve ROI on paid media investments.
• Apply advanced data-driven modeling techniques to inform decision making and solve complex business problems, including preprocessing multisource data and presenting complex information using data visualization techniques.
• Demonstrate the ability to use data, analytics, and insights to drive business impact.
• Ask insightful questions and suggest experimentation to drive incremental impact.
• Communicate findings effectively by telling succinct, data-driven stories tailored to stakeholders at various levels, from analysts to senior executives.
• Build predictive models and machine-learning algorithms.
• Analyze large datasets to discover trends and patterns.
• Preprocess structured and unstructured data.
• Present complex information using data visualization techniques.
• Propose solutions and strategies to business challenges that drive impact.

Requirements

• 5+ years of experience as a data scientist or in a related role, developing, deploying, and monitoring large analytic datasets and machine learning models.
• 2+ years of experience working with site/clickstream measurement, A/B testing, and industry measurement media platforms.
• Expertise in fundamental statistical concepts and selecting appropriate modeling techniques.
• Proficiency in Python/R (modeling) and SQL/Spark (data).
• Ability to prioritize and manage multiple tasks and projects simultaneously without sacrificing quality.
• Proficiency in analytical methodologies such as numerical optimization, econometric modeling, forecasting, machine learning, and text analytics.

Nice to Have

• Master's Degree or Ph.D. in Marketing Science, Econometrics, Statistics, Psychometrics, (Bio)Statistics, Applied Mathematics, Operations Research, or another quantitative field.
• Experience with cloud compute platforms such as Azure with Databricks.
• Familiarity with advanced methods such as customer lifetime value, media mix modeling (MMM), multi-touch attribution (MTA), consumer choice models, time-series forecasting, hierarchical bayes, panel-data methods, censored/truncated regressions, selection models, hazard/survival models, structural equation modeling, item response theory, latent class regression.

Qualifications

• Formal educational qualifications are not explicitly specified, but advanced degrees (Master's or Ph.D.) are preferred for competitive advantage.

Benefits & Perks

• GM offers a variety of health and wellbeing benefit programs including medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance, employee assistance program, GM vehicle discounts, and more.
• Compensation includes a base salary range of $125,000 - $205,100, with incentive pay based on company, job level, and individual performance.