Lead / Staff Data Scientist

Description

We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place.

We’re looking for an experienced Data Scientist who will help us build marketing attribution, causal inference, and uplift models to improve the effectiveness and efficiency of our marketing efforts. This person will also design experiments and help us drive consistent approach to experimentation and campaign measurement to support a range of marketing, customer engagement, and digital use cases.

This Lead Data Scientist brings significant experience in designing, developing, and delivering statistical models and AI/ML algorithms for marketing 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 statistical and machine learning 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 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.