Job Summary
As a Senior Data Scientist, you will lead initiatives to deliver actionable analytics that support acquisitions and cross-functional data solutions. This strategic role offers the opportunity to directly influence business outcomes and enhance our data products. You’ll be part of a collaborative team of engineers, analysts, product managers, and company leaders that leverage data to drive strategic decisions and strengthen our data product capabilities.
Responsibilities
Develop and lead the creation of predictive models to identify trends in our music catalog, focusing on metrics such as streams, playlist performance, follower growth, and release impact
Oversee the integration of internal Spotify data and external Viberate data to train models, ensuring robust and scalable data pipelines
Rigorously test and validate models to ensure their accuracy and reliability, enabling precise M&A decisions, such as identifying high-value catalog acquisitions
Expand model capabilities to analyze non-internal music, supporting broader acquisition strategies
Collaborate with the business to translate model insights into strategic data driven recommendations
Design and implement cross-functional dashboards that deliver actionable insights to product, A&R, and marketing teams, enhancing the utility of our data product
Drive innovation in music analytics by exploring advanced techniques, such as natural language processing for social sentiment analysis or graph-based models for artist networks
Partner with engineers, analysts, and product managers to elevate our data capabilities, providing mentorship to junior team members as the team grows
Navigate complex datasets, adapt to evolving priorities, and deliver insights that influence high-stakes business decisions
Qualifications
5+ years of experience as a Data Scientist, with a proven track record of delivering impactful models in music, entertainment, or a data-intensive industry
Advanced proficiency in Python, R, or similar programming languages, with expertise in machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
Deep understanding of predictive modeling, statistical analysis, and advanced techniques, including regression, clustering, and time-series forecasting
Demonstrated experience with APIs (e.g., Viberate) for data extraction and analysis, along with proficiency in managing data pipelines (e.g., BigQuery, Airflow)
Strong data engineering skills, with the ability to handle large, complex datasets and optimize for performance
Exceptional communication skills, capable of presenting complex models and insights to non-technical stakeholders, including executive leadership
A strategic thinker with a problem-solving mindset, comfortable working in a fast-paced environment with shifting priorities
Preferred: Direct experience with music data (e.g., streams, playlists, social metrics) or supporting M&A initiatives; familiarity with Looker or AI Platform is an advantage
Ideal: Exposure to advanced analytics methods, such as NLP, graph theory, or recommendation systems, demonstrating an ability to innovate
Pay Scale
$150,000 - $230,000 CAD per year depending on experience
