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Job Category
Products and Technology

Job Details

Salesforce is embarking on our own Digital Transformation to deliver success for our customers and accelerate our growth. As every Digital Transformation is also a Data Transformation, we're investing in scaling our data science capabilities in our Marketing Decision Science group.

We're looking for an experienced Data Scientist who will help us build predictive models and recommender systems using machine learning and statistical techniques to drive personalized marketing and customer experience.

This Data Scientist brings significant experience in designing, developing, and delivering statistical models and machine learning algorithms for targeting and digital optimization use cases on large-scale data sets in a cloud environment. They show rigor in how they prototype, test, and evaluate algorithm performance both in the testing phase of algorithm development and in managing production algorithms. They demonstrate advanced knowledge of machine learning and statistical techniques along with ensuring the ethical use of data in the algorithm design process. At Salesforce, Trust is our number one value and we expect all applications of statistical and machine learning models to adhere to our values and policies to ensure we balance business needs with responsible uses of technology.

Responsibilities

• As part of the Customer Modeling Data Science team within the Salesforce Marketing Data Science organization, develop machine learning algorithms and statistical models to drive effective marketing and personalized customer experience - e.g., propensity models, uplift models, next-best recommender systems, etc.
• 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.
• 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, computer science, industrial engineering and operations research, applied math, or other relevant quantitative field.
• 5-10+ 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.
• 5+ 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.

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