At Warner Music Group, we're a global collective of music makers and music lovers, tech innovators and inspired entrepreneurs, game-changing creatives and passionate team members. Here, we know that each talent makes our collective bolder and brighter. We are guided by four core principles that underpin everything we do across all our diverse businesses: Music is Everything:
Music is our passion, and we can never get enough. Tastes, trends, and tech will change, but great artists and songwriters will always be our driving force. Global Growth, Local Expertise:
Music is a global language. Through communication and collaboration, our success can come from anywhere and translate everywhere. Innovation and Insight:
Pushing the boundaries requires the best information and the boldest imagination. We use both to create the future. Empowered by People:
Like the artists we serve and the music they make, our differences make us stronger. This is a place where every talent can belong and build a career. We remain committed to Diversity, Equity, and Inclusion. We know it fosters a culture where you can truly belong, contribute, and grow. We encourage applications from people of any age, gender identity, sexual orientation, race, religion, ethnicity, disability, veteran status, and any other characteristic or identity. Consider a career at WMG and get the best of both worlds - an innovative global music company that retains the creative spirit of a nimble independent.
Job Title: Data Scientist
A little bit about our team: The Analysis & Insight team sits centrally and delivers clear and actionable recommendations across the business including the frontline & catalogue labels, commercial & finance.
Your role: You are a music lover who understands this unconventional industry; driven and innovative, you think out of the box and are always looking for new techniques to explore data and deliver insight.
Here you'll get to:
Pro-actively support the business by gathering data and, using advanced statistical techniques, communicate key insights that lead to strategic change Apply statistical and machine learning techniques to large datasets to uncover patterns, trends, and predictive insights Create compelling data visualisations to help communicate insight to non-technical stakeholders Ensure data accuracy and consistency by collaborating with data engineering teams Support WMUK by automating existing manual reporting Stay up-to-date with industry trends, emerging trends and best practices About you:
Data Science
Strong proficiency in Python and its associated data science libraries (e.g. Pandas, NumPy, scikit-learn, TensorFlow, PyTorch) and data visualisation libraries (e.g. Plotly, Dash) Strong knowledge of statistical analysis and data visualization techniques Strong knowledge of machine learning algorithms, including supervised and unsupervised Strong knowledge of machine learning interpretation, evaluation and explanation practices Data Engineering
Experience with data extraction, transformation, and processing Proficiency in SQL for data extraction and manipulation Experience designing, building, and maintaining ETL processes and data pipelines for datasets from various sources, including website scraping, social media APIs, and internal systems Experience with Docker and other relevant tools for deploying and scaling data pipelines and machine learning models a benefit Additional Technical Skills
Experience with Python web development frameworks, particularly Django Experience with Git for version control Familiarity with Snowflake or Databricks is a benefit, especially familiarity with Snowpark or PySpark Python libraries Experience with big data technologies and cloud platforms (e.g., AWS, Azure) is a benefit Familiarity with time series modelling techniques a benefit Soft Skills
Excellent problem-solving and critical thinking skills, with the ability to analyse complex datasets and derive meaningful insights Strong communication skills, both written and verbal, with the ability to present complex findings to technical and non-technical stakeholders Experience working and communicating with various non-technical stakeholders, including C-suite, social media managers, and commercial managers Highly organized, detail-oriented, and able to manage multiple projects and prioritise effectively Ability to stay updated on new trends, tools, and methodologies in data science and data engineering We'd love it if you also had:
Degree in Data Science, Computer Science, Statistics, or a related quantitative discipline might be helpful but not essential About us: As the home to Asylum, Atlantic, East West, Elektra, FFRR, Fueled by Ramen, Nonesuch, Parlophone, Rhino, Roadrunner, Sire, Warner Records, Warner Classics, #J-18808-Ljbffr