Senior Data Scientist, Warner Music Group

• 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 impactful insight
• Extensive 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 and practical application of statistical analysis and data visualization techniques
• Strong experience of a wide range of machine learning algorithms, including supervised & unsupervised
• Proven experience in machine learning model interpretation and evaluation with the ability to articulate model limitations and risks
• Significant experience with data extraction, transformation and processing large-scale datasets
• Advanced proficiency in SQL for complex data extraction, manipulation and optimization
• Demonstrable experience designing, building, and maintaining robust and scalable ETL processes and data pipelines for datasets from various sources (website scraping, social media APIs, internal systems)
• Experience with Docker and other relevant tools for deploying and scaling data pipelines and machine learning models is a strong advantage
• Additional Technical Skills:
• Experience with Python web development frameworks – Django, in particular, beneficial
• Experience with Git for version control and collaborative development
• Familiarity with Snowflake or Databricks, especially with Snowpark or PySpark Python libraries
• Experience with big data technologies and cloud platforms (e.g., AWS, Azure) a benefit
• Familiarity and practical experience with time series modelling techniques are a benefit
• Leadership & Soft Skills:
• Exceptional problem-solving and critical thinking skills, with a proven ability to tackle ambiguous challenges, analyse complex datasets, and derive actionable strategic insights
• Strong communication skills, both written and verbal, with the ability to articulate complex findings and influence technical and non-technical stakeholders at all levels, including C-suite
• Demonstrated experience working, influencing, and communicating effectively with various non-technical stakeholders at various levels
• Highly organized, detail-oriented, with proven ability to lead multiple projects, manage priorities effectively, and delegate where appropriate
• A proactive and curious mindset with a commitment to staying updated on new trends, tools, and methodologies in data science and data engineering, and sharing this knowledge with the team

Desirable

• The Data & Insight team work with the Frontline & Catalogue labels, Commercial & Finance teams on: track / artist performance and strategy, partner / competitor performance analysis, market trends, risks & opportunities. Sometimes as part of a team, sometimes solo but always delivering timely, clear and actionable insight and recommendations
• You will not only execute complex analyses but also lead data science work streams, guide junior team members, and help shape our data strategy
• Pro-actively support the business by gathering data and, using advanced statistical techniques, communicate key insights that lead to strategic change
• Anticipate stakeholder needs, developing tools and frameworks to provide data-driven insight and solutions to the business, particularly collaborating with the creator, paid media, and audience teams
• Apply sophisticated statistical and machine learning techniques to large, complex datasets to uncover patterns, trends, and predictive insights
• Champion the creation of compelling and intuitive data visualisations to effectively communicate complex insights to both technical and non-technical stakeholders, including senior leadership
• Ensure data accuracy, consistency, and governance by collaborating closely with data engineering teams, and providing guidance on data quality best practices
• Encourage the automation of existing manual reporting and processes, identifying opportunities for efficiency gains across the business
• Mentor and upskill members of the data team, fostering a culture of learning and development in advanced analytical techniques
• Stay at the forefront of industry trends, emerging technologies, and best practices in data science and machine learning, evaluating their potential application within our business