Data Science Specialist

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.