GM: Sr. Data Scientist, CRM

This role is categorized as hybrid. This means the successful candidate is expected to report to Warren, MI or Austin, TX three times per week, at minimum [or other frequency dictated by the business if more than 3 days].

The Marketing Applied Sciences team is responsible for developing analytics-driven solutions to help GM Marketing Organizations achieve their business goals. The Senior Data Scientist will work as part of this multi-disciplinary team that will be driving solution design, development, and deployment of analytic models in support of marketing strategies. They are knowledgeable in methodology and practice of marketing analytics with an emphasis on inferential and prescriptive methods. This individual has experience with website, email, and media measurement.  
 
This person will work closely with teammates in Marketing Applied Sciences and stakeholders in GM’s Marketing organization to ensure objective performance evaluation and optimization of media strategy. This senior data scientist will assist in the research and development of advanced marketing models, drawing insights, and creating scalable products across owned & paid channels. They will be part of a team focused on delivering future-focused, consumer-centric, prescriptive solutions that allow GM to stay proactive and nimble in our exciting transition to EVs 

What You’ll Do

• Work on a diverse, cross-functional team (technical and non-technical) to help implement high-impact, data-driven solutions to address business challenges in the vehicle brand marketing teams, ensuring that project deliverables fulfill business needs and timing.  
• Possess contextual business knowledge and functional domain expertise in the advertising and media space as well as familiarity with marketing media measurement techniques including site/clickstream measurement, A/B testing, and various industry measurement media platforms.   
• Partner with CRM, Marketing, and Data Science teams to design and execute advanced measurement frameworks that evaluate campaign effectiveness, incremental revenue impact, and consumer engagement across lifecycle stages. 
• Apply advanced data-driven modeling techniques to inform decision making and solve complex business problems: preprocessing multisource data; and presenting complex information using data visualization techniques.   
• Demonstrate an ability for using data, analytics, and insights driving business-impact.   
• Exhibit a perspective of constrained curiosity, asking why, and suggesting experimentation to drive incremental impact.   
• Effectively communicate through telling a succinct, data-driven story in any forum, tailoring delivery to a wide range of stakeholder levels from analyst to senior executive.   
• Apply advanced modeling and analytics techniques to optimize campaign targeting, channel strategy, and customer journey orchestration. 

Your Skills & Abilities (Required Qualifications)

• 5+ years of experience as a data Scientist or in a related role, developing, deploying, and monitoring performance of large analytic data sets and machine learning based models  
• 2+ years of experience working with CRM, marketing analytics, or lifecycle management. 
• Expertise with fundamental statistical concepts and considerations for selecting an appropriate modeling technique.  
• Expertise with statistical concepts and methods for campaign measurement, including uplift/net lift modeling, treatment/control designs, and causal inference. 
• Proficient writing Python/R (modeling) and SQL/Spark (data), working with Pandas, StatsModels, PYMC, TensorFlow, Pytorch, Spark/ML, sklearn, numpy and related packages.   
• Ability to prioritize and manage multiple tasks and projects at once without sacrificing quality.   

What Can Give You a Competitive Advantage (Preferred Qualifications)   

• 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 experience being especially valuable.   
• Familiarity with advanced methods such as: customer lifetime value, media mix modeling (MMM), multi-touch attribution (MTA), consumer choice  (multinomial logit), time-series forecasting, hierarchical bayes, panel-data methods (fixed/random effects), censored/truncated regressions, selection models, non-random treatment effects, hazard /survival models, structural equation modeling, item response theory, latent class regression.  
• Prior experience with paid, earned, and owned media and/or marketing analytics