Staff Data Scientist, Customer Experience

Salesforce, Inc.
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Job Description

We are looking for an experienced data scientist to support the Customer Experience team at Slack. At Slack, our mission is to make people’s working lives simpler, more pleasant, and more productive. The Customer Experience team lives this every day, providing a delightful experience to our customers.

In this role, you will work closely with the Customer Experience organization to understand and improve the experience people have with Slack across every stage of the customer journey. You will have the opportunity to influence key business and product decisions through your analysis and insights. Your credibility will be strengthened through deep technical skills, strong business sense, and a clear dedication to improving our customers’ experiences. You will bring a solid understanding of SaaS businesses, forecasting models, and ways to process natural language. You can also tell compelling stories with data.

Slack has a positive, diverse, and supportive culture—we look for people who are curious, inventive, and work to be a little better every single day. In our work together we aim to be smart, humble, hardworking and, above all, collaborative. If this sounds like a good fit for you, why not say hello?

What you will be doing

  • Apply various data science methods to understand usage patterns of Slack Support 
  • Perform evidence-based evaluations of the most important drivers of satisfaction with Slack and Slack Support
  • Build out key success metrics and reporting for the Customer Experience organization
  • Prototype foundational data pipelines and partner with the data engineering organization to elevate these into canonical sources of truth for Customer Experience metrics
  • Identify and clearly communicate potential opportunities to improve the experience of people using Slack
  • Evangelize evidence-based decision making by partnering with key decision makers and driving general accessibility of data and insights
  • Organize disparate facts and analyses into a coherent narrative that evaluate the success of and influence product and support strategy

What you should have

  • A passion for customer support and the role it plays in making a customer-centric team successful
  • Expertise in scoping work requested by diverse sets of stakeholders
  • Data science or engineering experience doing data science or quantitative analysis, with preferred experience in settings with multiple consumer user types, such as a marketplace or productivity or collaboration tools. 
  • Expertise in at least one programming language for data analysis (e.g. Python, R, Scala)
  • Experience working with data technologies that allow analysis of large amounts of data (e.g. Spark, Presto, Hive, Hadoop, etc). Familiarity with Apache Airflow is a plus.
  • Comfortable and skilled at written and verbal communication to varied audiences
  • Experience collaborating with and influencing cross functional partners
  • Experience in building advanced data pipelines and designing data scheme and table infrastructure
  • Experience in cleaning sets of data so accurate decisions and forecasts can be made
  • Plus: An advanced degree (MS, PhD) in a quantitative field (e.g. Computer Science, Economics, Physics)
  • Plus: Experience with statistical and machine learning methods to build descriptive and predictive models

Company Info.

Salesforce, Inc.

Salesforce is an American cloud-based software company headquartered in San Francisco, California. It provides customer relationship management (CRM) service and also provides enterprise applications focused on customer service, marketing automation, analytics, and application development.

  • Industry
    Consulting,Cloud computing,Computer software
  • No. of Employees
    73,541
  • Location
    Salesforce Tower, Mission Street, San Francisco, California, USA
  • Website
  • Jobs Posted

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Salesforce, Inc. is currently hiring Staff Data Scientist Jobs in United States with average base salary of $120,000 - $190,000 / Year.

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