Lead Data Scientist

fulltime

Employment Information

Job Details

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.

For roles in San Francisco and Los Angeles: Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.

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Equal Opportunity Statement.

At Salesforce we believe that the business of business is to improve the state of our world. Each of us has a responsibility to drive Equality in our communities and workplaces. We are committed to creating a workforce that reflects society through inclusive programs and initiatives such as equal pay, employee resource groups, inclusive benefits, and more. Learn more about Equality at www.equality.com and explore our company benefits at www.salesforcebenefits.com.

Salesforce is an equal employment opportunity and affirmative action employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status. Know your rights: workplace discrimination is illegal. Salesforce does not accept unsolicited headhunter and agency resumes. Salesforce will not pay any third-party agency or company that does not have a signed agreement with Salesforce.

Salesforce welcomes all.

In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. More details about our company benefits can be found at the following link: https://www.salesforcebenefits.com.

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