This Role;

Our vision is to use the best of AI, predictive modeling, segmentation and decisioning to serve the Salesforce Marketing organization. We are seeking a Senior Data Scientist who has a strong background in machine learning (ML), specifically in the areas of next best content recommendations, prediction of best email frequency, and resolving next best journey for the subscriber. Our goal is to develop predictive models that resolve best email to send at the best time to our subscribers, ensuring the ethical use of data in the algorithm design process.

At Salesforce, Trust is our number one value, and we ensure our implementation will be trained to prevent bias, preserve privacy, and ensure cultural sensitivity.

Responsibilities

Work with large and sophisticated data sets to solve a wide array of challenging problems using different analytical, statistical, and machine learning approaches
Own the full lifecycle of model development from ideation and data exploration, algorithm design, validation, and testing. Work closely with data engineers to develop modeling data sets and pipelines; deploy models in production, setup model monitoring and in-production tuning processes
Partner with product and engineering teams to understand existing product instrumentation and help bridge gaps in data streams to assist data science initiatives
Analyze product usage patterns to better understand customer behavior including acquisition, engagement, conversion, and retention
Architect and implement AI/ML models to recommend personalized email content
Leverage powerful GenAI capabilities to drive optimization in the areas such as audience segmentation, creative optimization, personalization, lifecycle marketing and media mix modeling
Drive A/B and multivariate tests and design of feature-level experiments to validate hypotheses and influence product development decisions
Partner with multi-functional teams and leaders to identify new opportunities requiring the use of modern analytical and modeling techniques
Communicate insights and recommendations to marketing leaders and influence strategic decision-making.

Required Skills:
4+ years of experience in Product Data Science, including in-depth experience with experimentation. Experience with predictive modeling, machine learning, and experimentation/causal inference methods
Experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), and/or statistical/mathematical software (e.g., R)
4-6+ years of experience using advanced statistical and machine learning techniques such as clustering, linear and logistic regressions, PCA, gradient boosting machines (GBM), support vector machines (SVM), neural networks (e.g., ANN, RNN, CNN), and other deep learning algorithms (e.g., Wide & Deep). Must have multiple, robust examples of using these techniques to support marketing efforts and to solve business problems on large-scale data sets
Experience using cloud platforms such as GCP and AWS for model development and operationalization is preferred
Experience translating business questions into data analytics approaches
Experience crafting data visualizations and storytelling to efficiently communicate analysis results to both technical and non-technical audiences
Experience developing and operationalizing consistent approaches to experimentation, using appropriate statistical techniques to reduce bias and interpret statistical significance
* Possess natural curiosity and technical competence, being capable of asking critical questions and always ready to address any challenges

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