About the Role
We’re looking for a curious, analytical, and detail‑driven Data Scientist to join our Commercial data team. In this role, you’ll begin with a strong analytics focus, laying the foundations for future predictive and optimisation modelling, while working closely with both technical and commercial teams to ensure data is used effectively to improve performance and decision‑making. You’ll translate complex datasets into clear, actionable insights that support key areas such as Sales, Operations, and Finance, and you’ll thrive if you enjoy solving real‑world commercial problems and collaborating cross‑functionally in a fast‑paced environment.
Key Responsibilities
Develop decision‑support tools and dashboards analysing sell‑through, reach, revenue, and market trends.
Build analytical frameworks that evolve into predictive or optimisation models.
Support prediction and optimisation work including revenue, pricing, and inventory forecasting; listener segmentation; and ad‑scheduling.
Contribute to A/B testing, causal inference, and uplift modelling.
Build and maintain Tableau dashboards across revenue management, digital audio, and competitions.
Automate reporting pipelines and promote a self‑serve analytics culture.
Present insights clearly to technical and non‑technical audiences.
Collaborate with commercial, digital media, revenue management, and consumer competitions teams.
Translate business questions into data‑driven use cases such as pricing, segmentation, churn, and optimisation.
Partner with Engineering and Platform teams to integrate models into systems.
Qualifications & Experience
Proven experience in data analytics or data science, ideally within media, audio, digital, or revenue‑driven environments.
Strong experience with Python, SQL, and ML toolkits such as scikit‑learn and XGBoost.
Experience with modern cloud data stacks (., Snowflake, BigQuery).
Comfortable working with Git, Jupyter, Airflow, and agile practices.
Strong grounding in BI tools such as Tableau or Power BI.
Experience with pricing, supply/demand dynamics, inventory management, or yield optimisation.
Familiarity with modern tooling such as AutoML, vector databases, APIs, or cloud platforms.
Strong relationship‑building skills across commercial, product, and operational teams.
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