Staff Data Scientist 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 CategoryDataJob DetailsSlack is looking for an experienced data scientist to join our Business Analytics team. In this role, you will be responsible for leveraging data to help drive the growth and success of the Slack Business Unit. The ideal candidate is a strong communicator, can operate independently with minimal guidance, has a growth mindset, collaborates effectively with others, and biases towards action and impact.The Business Analytics team is focused on helping executives and other key decision makers across the company make better decisions using data. We work closely with Data Engineering and Business Intelligence, other Data Scientists at Slack and our partners in Product, Engineering, and the Slack Distribution teams to identify growth opportunities, craft narratives that deepen our understanding of the business, forecast future performance, and build predictive models to effect positive business outcomes.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
Partner with Slack Distribution teams to understand the drivers of our business and accelerate growth
Synthesize insights into crisp narratives and present to senior leadership 
Develop frameworks for identifying patterns/trends in customer behavior and implement them in predictive scoring models
Empower others to be self-sufficient in data by building self-service tools and reports to drive awareness and understanding of key metrics
Work with our Data Engineering and Business Intelligence teams to build core data models that power operational and exploratory data analyses
What you should have
4+ years of professional industry experience doing quantitative analysis
A degree in Economics, Physics, Statistics, Math, or other quantitative field (advanced degrees are a plus)
Proficient in SQL and at least one programming language for data analysis (e.g. Python, R)
Experience with statistical and machine learning methods to build descriptive and predictive models
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