Staff Data Scientist Enterprise at Slack

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.Job CategoryProducts and TechnologyJob DetailsWe are looking for an experienced data scientist to support the enterprise product area at Slack. The enterprise ecosystem is a critical component of Slack’s strategy to become an even more convenient and powerful tool for collaboration for full spectrum of async and synchronous work. It provides our grid customers with rich and enhanced experience on our platform with targeted features and integrations. In this role, you will work closely with the enterprise product organization to understand and improve the product experience of enterprise segment. As Slack builds out its next generation of enterprise experiences, you’ll work on unearthing insights that will help point to the direction of future enhancements. You will also help establish the foundational data infrastructure to enable success measurements. You will partner with researchers, designers, and engineers to uncover user experience gaps and opportunities. 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. What you will be doing
Apply various data science methods to understand usage patterns of grid customers 
Perform evidence-based evaluations of the most important drivers of increased adoption of the enterprise specific features
Build out key success metrics and reporting for the enterprise product organization
Prototype foundational data pipelines and partner with the data engineering org to elevate these into canonical sources of truth for enterprise metrics
Identify and clearly communicate potential opportunities to improve the end user experience
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 strategy
What you should have
5+ years of 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. 
An advanced degree (MS, PhD) in a quantitative field (e.g. Stats, Maths, Computer Science, Economics, Physics, etc) a plus
Expertise in at least one programming language for data programming (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.
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
A related technical degree required 
Plus: Experience with statistical and machine learning methods to build non production models
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