Responsibilities
* As part of the Marketing Effectiveness Data Science team within the Salesforce Marketing Data Science organization, develop statistical and machine learning models to improve marketing effectiveness - e.g., marketing attribution models, causal inference models, uplift models, etc.
* Develop optimization and simulation algorithms to provide marketing investment and allocation recommendations to improve ROI by optimizing spend across marketing channels.
* Own the full lifecycle of model development from ideation and data exploration, algorithm design and testing, algorithm development and deployment, to algorithm monitoring and tuning in production.
* Design experiments to support marketing, customer experience, and digital campaigns and develop statistically sound models to measure impact. Collaborate with other data scientists to develop and operationalize consistent approaches to experimentation and campaign measurement.
* Be a master in cross-functional collaboration by developing deep relationships with key partners across the company and coordinating with working teams.
* Constantly learn, have a clear pulse on innovation across the enterprise SaaS, AdTech, paid media, data science, customer data, and analytics communities.
Required Skills
* Master’s or Ph.D. in a quantitative field such as statistics, economics, industrial engineering and operations research, applied math, or other relevant quantitative field.
* 8+ years of experience designing models for marketing optimization such as multi-channel attribution models, customer lifetime value models, propensity models, uplift models, etc. using statistical and machine learning techniques.
* 8+ years of experience using advanced statistical techniques for experiment design (A/B and multi-cell testing) and causal inference methods for understanding business impact. Must have multiple, robust examples of using these techniques to measure effectiveness of marketing efforts and to solve business problems on large-scale data sets.
* 8+ years of experience with one or more programming languages such as Python, R, PySpark, Java.
* Expert-level knowledge of SQL with strong data exploration and manipulation skills.
* Experience using cloud platforms such as GCP and AWS for model development and operationalization is preferred.
* Must have superb quantitative reasoning and interpretation skills with strong ability to provide analysis-driven business insight and recommendations.
* Excellent written and verbal communication skills; ability to work well with peers and leaders across data science, marketing, and engineering organizations.
* Creative problem-solver who simplifies problems to their core elements.
* B2B customer data experience a big plus. Advanced Salesforce product knowledge is also a plus.