We are seeking an experienced data scientist to join our team and contribute to our foundation product areas at Slack. The Foundation lies at the core of Slack’s user experience and is pivotal to our business and product strategy of being the ultimate hub for work collaboration. It empowers users with rich features and integrations, unlocking the true potential of Slack.
In this role, you will collaborate closely with the Foundation product organization to enhance the product experience for Slack users. As we develop the next generation of core user experiences, your role will involve uncovering insights and painting a comprehensive picture of user needs and adoption within Slack. Additionally, you will play a key role in establishing the analytics infrastructure necessary to measure various components of Foundation products. Your collaboration with researchers, designers, and engineers will help identify user experience gaps and unearth new opportunities.
At Slack, we foster a positive, diverse, and supportive culture, seeking individuals who are curious, innovative, and committed to continual improvement. Our approach is characterized by intelligence, humility, hard work, and above all, collaboration.
Responsibilities:
Apply various data science methods to analyze usage patterns of Foundation products.
Conduct evidence-based evaluations of key drivers of feature adoption and user retention.
Develop key success metrics for different stages of product life cycles to ensure timely measurement of product health and successes.
Prototype foundational data pipelines and collaborate with the data engineering team to establish canonical sources of truth for Foundation metrics.
Identify and effectively communicate opportunities to enhance core user experiences.
Promote evidence-based decision-making by partnering with product decision-makers and facilitating broader access to data and insights.
Synthesize disparate facts and analyses into a cohesive narrative that evaluates the success of and influences product strategy.
Requirements:
5+ years of experience in data science or engineering, with a preference for experience in settings with multiple consumer user types (e.g., marketplace, productivity tools).
Advanced degree (MS, PhD) in a quantitative field (e.g., Computer Science, Economics, Physics, Mathematics) is a plus.
Proficiency in at least one programming language for data analysis (e.g., Python, R, Scala).
Experience with data technologies for analyzing large datasets (e.g., Spark, Presto, Hive, Hadoop); familiarity with Apache Airflow is advantageous.
Strong written and verbal communication skills tailored to diverse audiences.
Track record of collaborating with and influencing cross-functional partners.
Experience in building advanced data pipelines and designing data schema and table infrastructure.
Bonus: Experience with statistical and machine learning methods for building descriptive and predictive models.