Decision Scientist - Self-Service Experience
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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.
Trust is our #1 value at Salesforce. The Data and Analytics (DnA) team powers that value and propels Salesforce growth by providing trusted data, insights, and artificial intelligence that enables us to make more informed decisions in every dimension. We develop tools for financial forecasting, assessing customer health, uncovering adoption insights, data curation, and more, all designed to support another core value at Salesforce... customer success.
The DnA team is organized into four Pillars:
- The T&P (Technology and Product) Pillar of the DnA team serves as analytical partners and trusted advisors to General Managers of Salesforce business lines, as well as to product managers and their maker teams. We empower GMs to grow adoption, retention, and ACV. We empower makers to build easy-to-use and performant products that unlock value
- The Success Pillar exists to drive outcomes for our customers and Salesforce, using the collective mind of DnA to create delightful digital experiences that dazzle stakeholders, boost productivity, and foster a culture of continuous learning and growth
- The Sales Pillar helps Sellers and Sales Leaders see the future by providing a predictable view of the business. We develop a scalable, data-driven way to plan our seller capacity, sales territories, and long-range plan. Our team will directly increase AE productivity, increase our margin, and build a foundation for a strong Salesforce
- The Transformation Pillar exists to measure, inform, and therefore manage change across the enterprise for initiatives such as margin
We are hiring Decision Scientists across all four Pillars. As a Decision Scientist, you will deliver key insights and analyses that help Salesforce leaders and teams make key decisions that shape strategy, operations, the way we develop products, the way we sell, the way we interact with customers, and much more. You will acquire deep knowledge and understanding of Salesforce products and business goals, build and manage cross-functional relationships, and communicate through digestible, relevant, and actionable storytelling. You will manage data and insights as a product, partnering with data product managers, data engineers, data scientists, ML engineers, visualization engineers, and many other DnA teammates to deliver data products, such as dashboards, ML apps, automation, and much more. You will use business thinking, engineering skills, statistical techniques, and data science practices - such as experimentation, forecasting, clustering, etc. - to wrangle data and deliver relevant and trustworthy insights.
Learn more about our culture:
Our Story & Core Values: Bringing People together changes everything
Women Leadership: How Salesforce is nurturing women tech leaders of the future
Everyone can be a Trailblazer with Salesforce
Why Bring Your Kids to Work Day is so much more than one day of fun
Success in the Role: What would it look like?
As a Decision Scientist, you are
- A hands-on analyst
- You will generate insights (e.g., performance drivers, retention analysis, behavioral personas and much more) to accelerate business growth. This requires acquiring and cleaning data from multiple sources, structuring and building data models, analyzing to generate insights, and distributing those insights to business leaders.
- You have an experimentation mindset. You are excited about understanding the business problem and your internal users, focusing on outcome not output, and iterating to achieve the business outcome through an experimental approach.
- A strategic problem solver
- You understand the “big picture” context of your business and analyze data with business a mentality
- You translate business challenges into an analytical plan; you think practically and creatively to craft quick, effective solutions to problems
- A relationship builder
- You will develop relationships and collaborate with teams to understand business problems and create and implement an analytical plan
- You are comfortable delivering insights to an executive audience
- A cross-functional partner
- You will partner with data engineers and product managers to instrument, acquire, develop, and structure data assets that are critical to measuring the success of our products
- Identify internal and external collaborators to curate data assets and produce actionable data insights and products
- A data champion/A data-lover at heart/data evangelist
- You will support the expansion of Salesforce data culture by growing new relationships, hosting learning sessions, integrating or designing new tools, and improving team processes
- 2-10 years of experience in data analytics or data science or a master’s degree in data science, statistics, applied mathematics, analytics or a related field, or equivalent alternative education, skills, and/or practical equivalent experience
- You are proficient in common analytical programming languages (e.g. Python or R) and SQL
- You have a strong understanding of statistical and machine learning methods such as A/B testing, experiment design, causal inference, quasi-experimental methods, common ML models, recommendation systems etc.
- You are familiar with end-to-end data development, including data model design, quality review, deployment, and maintenance
- You are proficient in telling data stories in a wide range of formats, including slides, charts, and dashboards (e.g. Tableau), and can coherently articulate the business impact of your insights product
- You are able to plan projects in detail, set schedules, coordinate resources across product, data, and engineering teams, complete projects end-to-end, and make sure timelines and quality expectations are met.
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