Senior Scientist - Experimentation

Job Description

This role is based remotely but if you live within a 50-mile radius of an office [Atlanta, Austin, Detroit, Warren, or Mountain View], you are expected to report to that location three times a week, at minimum.

The Role

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.
• Bring strong contextual business knowledge and domain expertise in advertising, paid media, and digital marketing, including deep 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: 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.
• You build predictive models and machine-learning algorithms.
• You analyze large amounts of information to discover trends and patterns.
• Undertake preprocessing of structured and unstructured data.
• Present complex information using data visualization techniques.
• Propose solutions and strategies to business challenges that drive business impact

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 site/clickstream measurement, A/B testing, and various industry measurement media platforms.
• Expertise with fundamental statistical concepts and considerations for selecting an appropriate modeling technique.
• Proficient writing Python/R (modeling) and SQL/Spark (data).
• Ability to prioritize and manage multiple tasks and projects at once without sacrificing quality.
• Proficient in one or more analytical methodologies such as numerical optimization, econometric modeling and forecasting, machine learning and text analytics.

Additional Job Description

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 analytic.

This job is not eligible for relocation benefits. Any relocation costs would be the responsibility of the selected candidate.

Compensation:

• The expected base compensation for this role is: $125,000- $205,100. Actual base compensation within the identified range will vary based on factors relevant to the position.
• Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
• Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE. DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP NOW OR IN THE FUTURE. THIS INCLUDES DIRECT COMPANY SPONSORSHIP, ENTRY OF GM AS THE IMMIGRATION EMPLOYER OF RECORD ON A GOVERNMENT FORM, AND ANY WORK AUTHORIZATION REQUIRING A WRITTEN SUBMISSION OR OTHER IMMIGRATION SUPPORT FROM THE COMPANY (e.g., H-1B, OPT, STEM OPT, CPT, TN, J-1, etc.)

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