Principal Product Data Scientist
| Company | Slack |
|---|---|
| Location | Seattle, WA, USA, San Francisco, CA, USA, Chicago, IL, USA, New York, NY, USA, Denver, CO, USA, Atlanta, GA, USA |
| Salary | $192200 – $334600 |
| Type | Full-Time |
| Degrees | Bachelor’s |
| Experience Level | Expert or higher |
Requirements
- 9+ years of experience in data science or quantitative analysis, preferably in technology product development or enterprise software.
- A related technical degree required; an advanced degree (MS, PhD) in a quantitative field (e.g., Mathematics, Economics, Statistics, Physics, Quantitative Psychology, Engineering, etc.) is a strong plus.
- Expertise in at least one programming language for data science (e.g., Python, R).
- Experience working with large-scale data technologies (e.g., Spark, Presto, Hive, Hadoop). Expertise in Apache Airflow is a strong plus.
- Strong executive communication skills, with the ability to translate complex data into clear, actionable insights.
- Cross-functional collaboration and influencing skills, with a track record of impacting decisions at both strategic and executional levels in a large corporate environment.
- Experience designing advanced data pipelines and schemas for scalability and efficiency.
- Strong statistical and machine learning knowledge, with experience building descriptive and predictive models.
- Expertise in DS measurement methodologies, with the ability to translate technical data into meaningful takeaways for non-technical stakeholders.
Responsibilities
- Apply advanced data science techniques to analyze Slack product usage patterns, identifying what’s working, what’s not, and opportunities for improvement.
- Conduct evidence-based evaluations to determine key drivers of Slack’s product growth.
- Define and report key success metrics, effectively communicating insights to Slack and Salesforce leadership to enable executive level decision making and follow-ups.
- Synthesize insights across different product areas and business outcomes, identifying correlations and causal relationships that drive success.
- At principal level, Serve as a domain expert in product data science, guiding best practices and advancing data science methodologies and operations.
- Champion evidence-based decision-making, making data and insights accessible and scalable for stakeholders at all levels.
Preferred Qualifications
- An advanced degree (MS, PhD) in a quantitative field (e.g., Mathematics, Economics, Statistics, Physics, Quantitative Psychology, Engineering, etc.) is a strong plus.
- Expertise in Apache Airflow is a strong plus.