Staff Data Scientist - Platform

What You'll Do

• Analyze large datasets to identify bottlenecks and propose actionable solutions to improve platform performance.
• Develop recommendations to optimize Spotify’s platform performance, reliability, and scalability.
• Collaborate with engineering and product teams to integrate data science insights into the development of Spotify’s platforms.
• Define and measure key performance metrics for platform reliability, scalability, and efficiency.
• Partner with leadership to identify high-impact opportunities and prioritize data science projects that drive platform innovation.
• Serve as a leader and trusted advisor for data science applications in platform development.
• Communicate complex technical findings to diverse stakeholders, including executives and non-technical teams.
• Provide technical mentorship to data scientists and analysts within the team.
• Advocate for best practices in data science, including reproducibility, and ethical AI considerations.
• Explore cutting-edge technologies and methodologies to enhance Spotify’s platform capabilities.
• Stay informed on trends in data science, distributed systems, and cloud computing to influence the company’s long-term platform strategy.

Who You Are

• Master’s or Ph.D. in Data Science, Computer Science, Statistics, or a similar field.
• 8+ years of experience in data science, machine learning, or applied statistics, with a focus on large-scale systems or infrastructure.
• Proficiency in relevant tools such as Python, R, or BigQuery, and experience with distributed computing.
• Comfort with machine learning frameworks and statistical modeling techniques.
• Outstanding problem-solving skills with the ability to tackle ambiguous technical challenges.
• Strong communication and presentation skills, with an emphasis on storytelling with data. Leadership and collaboration skills, with a proven ability to influence cross-functional teams.
• Preferred qualifications: deep understanding of platform infrastructure (including distributed systems, cloud platforms, and SRE principles), proven track record of deploying data science solutions in production environments at scale, experience working with time-series data, anomaly detection, and forecasting in operational systems, familiarity with Google Cloud Platform (GCP).

Where You'll Be

• This role is based in Stockholm or London.
• We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home. We ask that you come in 3 times per week.