Description:
We are seeking an Experienced Data Scientist with deep technical expertise and a passion for the music industry. This role involves working with large-scale datasets from various streaming platforms and music APIs, designing robust databases, and building models to drive insights that enhance decision-making for artists, labels, and music investors. You will also develop and manage complex data pipelines, ensuring accuracy and scalability.
Key Responsibilities
Data Integration & API Management:
- Extract, clean, and integrate data from music APIs (Spotify, Apple Music, YouTube, Deezer, and more).
- Automate workflows for data collection using APIs and third-party platforms.
- Ensure seamless integration with internal systems and databases.
Database Management:
- Design, manage, and optimize SQL-based databases and NoSQL systems (e.g., MongoDB).
- Build scalable data pipelines to handle streaming and transactional data efficiently.
Data Analysis & Modeling:
- Perform exploratory data analysis to uncover trends and actionable insights in music data.
- Develop machine learning models for audience segmentation, song performance prediction, and music asset valuation.
- Implement recommendation systems tailored for music content and user behavior.
Visualization & Reporting:
- Create dynamic dashboards and reports using tools like Power BI, Tableau, or custom-built solutions.
- Provide clear, visual presentations of insights for non-technical stakeholders, including artists and investors.
Innovation & Strategy:
- Stay updated on the latest tools, techniques, and trends in data science and music analytics.
- Propose innovative solutions to optimize music catalogs, predict trends, and drive revenue growth.
Required Skills & Qualifications
Education:
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field.
Technical Proficiency:
- Strong programming skills in Python and R, with expertise in data manipulation (pandas, NumPy).
- Advanced SQL skills for managing relational databases and optimizing queries.
- Hands-on experience with NoSQL databases (e.g., MongoDB, Cassandra).
- Familiarity with music-specific APIs (Spotify, YouTube, Deezer, etc.) and RESTful API integration.
- Expertise in machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
- Experience with big data platforms like Hadoop, Spark, or AWS for scalable analytics.
Music Domain Knowledge:
- Experience working with streaming analytics, audio feature analysis, or music metadata.
- Familiarity with tools like Librosa for audio signal processing is a plus.
Soft Skills:
- Exceptional problem-solving skills with a creative mindset.
- Strong communication skills for presenting technical findings to non-technical stakeholders.
- A passion for the music industry and its evolving data landscape.
Preferred Experience
- 5+ years of professional experience in data science, with at least 2 years focusing on music or entertainment data.
- Proven track record of designing and deploying data pipelines and predictive models.
- Prior experience working with cross-functional teams in a fast-paced environment.