Sr. Data Scientist
Slack is hiring an experienced data scientist on our Research & Analytics team. You’ll join our team of experts using a variety of data science and research methods to partner with key decision makers within the company. You’ll craft narratives that help us understand our users and our product and inform and influence decisions.
As an experienced data scientist, you will help to make Slack’s Research + Analytics team best-in-class by advocating for and implementing changes to process, tools, and systems. You will be a strong partner to researchers with varying backgrounds, including design researchers, market researchers, and survey scientists.
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
- Partnering closely with our “Platform” Product team to explore and understand how external services bring value to Slack.
- Applying various data science methods such as causal inference, experiments, machine learning, modeling, and forecasting to understand the most important aspects of our product, users, and business.
- Organizing disparate facts and findings into powerful narratives that have the broadest possible application within Slack.
- Evangelizing evidence-based decision making by partnering with key decision makers, and driving general accessibility of data and insights.
- Identify and drive improvements to the execution of the full Research + Analytics team through standardization of process and authoring best practices.
What you should have
- 5+ years of professional industry experience doing quantitative analysis. An advanced degree (MS, PhD) in a quantitative field (e.g. Computer Science, Econometrics, Physics) a plus.
- A consistent record of using product data to drive product, sales, and/or marketing teams to achieve ambitious goals and influencing outcomes.
- The ability to clearly and effectively communicate the results of complex analysis to a broad audience
- Expertise in at least one programming language for data analysis (e.g. Python, R).
- Expertise in designing and testing experiments.
- Experience working with data technologies that allow effective storage and analysis of large amounts of data (e.g. Hadoop, Hive, Spark, Presto, S3, etc).