Slack is looking for experienced data scientists to join our Product Analytics team and help drive the understanding, growth, and success of Slack. You'll have deep technical skills and a real passion for helping Slack make data-informed decisions. You'll be fearless, independent, and excited about having a big impact in a growing team.
You will partner closely with our Product and Engineering team to craft narratives, find insights, and provide recommendations. Data scientists are embedded in our Product teams to drive data-informed product development, and to work closely with other cross-functional teams such as Data Engineering & Business Intelligence.
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
● Use data to influence the direction of team roadmaps and inform business decisions
● Deepen our understanding of our product, our users, and our business through data
● Work with partner teams to define goals and identify metrics that describe our product through data
● Inspire self-serve data use by building dashboards and reports to drive awareness and understanding of metrics
● Partner with Data Engineering and IT to author and develop core data sets that empower operational and exploratory analyses
● Work cross-functionally to develop common practices and team playbooks for data science at Slack
What You Should Have
● 6+ years of professional industry experience doing quantitative analysis
● A proven track record of using analysis to impact key business or product decisions
● The ability to clearly and effectively communicate the results of complex analyses
● Experience writing production datasets in SQL/Hive OR building internal/production data tools for ETL, experimentation, or exploration in a scripting language (Python, R, etc.)
● A deep understanding of basic statistical applications and methods (experimentation, probabilities, regression)
● Experience in software engineering, data engineering, consulting, or academic research a plus