at Salesforce in Chicago, Illinois, United States
Job Description
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Job CategoryData
Job Details
About Salesforce
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.
Overview of the Role:
Slack (a Salesforce company) is looking for a data professional who can lead Slack's data science teams through its next chapter of growth. As the Vice President, Data Science, reporting to the COO, you will own the holistic data strategy for Slack, leading a team across business insights, data science, data engineering, product analytics, experimentation, and analytical tooling. This team partners closely with cross-functional stakeholders to provide critical business insights across sales, customer success, product, design, engineering and more.
Responsibilities:
Lead Slack's strategic direction and vision for data science, business analytics, and data engineering functions, building partnerships with functional stakeholders across Sales, Product, Marketing, and Go-To-Market Operations.
Partner with senior leadership across all of Salesforce to identify Slack's business challenges and opportunities, and translate them into actionable, integrated, data-driven solutions.
Champion a data-driven culture by fostering collaboration and common data literacy across data teams and business functions.
Oversee the recruitment, development, and management of a high-performing global team of data scientists, analysts, and data engineers.
Develop and implement a robust data governance framework to ensure data quality, security, and compliance.
Design and build scalable data infrastructure and platforms to support enterprise-wide data needs.
Drive the development and implementation of advanced analytics models and machine learning algorithms to extract valuable insights from data that drive the business forward.
Communicate complex data analysis and findings effectively to both technical and non-technical audiences.
Stay abreast of emerging data trends and technologies and champion their adoption within the organization.
Qualifications:
15+ years of experience in data science or data engineering leadership, with demonstrated success in applying advanced analytics techniques to solve real-world problems.
Established track record of building and leading high-performing data teams, fostering a culture of collaboration, accountability, and knowledge sharing.
In-depth understanding of modern data governance, security, and compliance best practices, with the ability to balance data accessibility with data integrity for data-driven projects.
Proven experience designing and implementing data infrastructure and platforms to support large-scale data science and analytics workloads (e.g., data lakes and data warehouses).
Proficiency in advanced analytics techniques and machine learning algorithms, including natural language processing, time series analysis, and other relevant methods.
Excellent communication, collaboration, and presentation skills, with the ability to translate complex analytical concepts into clear and actionable insights for diverse audiences (business to technical).
Strategic thinking and problem-solving abilities, with a strong focus on innovation and staying ahead of the curve in data and analytics.
Strong business acumen and a solid understanding of SaaS business processes and industry trends.
A related technical degree required.
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