Data Science Intern developing and supporting automation tools for optical systems at Nokia. Collaborating within a Global Agile team to enhance productivity and data analysis capabilities.
About the role
- Data Scientist at Warner Music Group uncovering listener behaviors through advanced statistical methods. Building predictive models and optimizing marketing campaign impact based on data-driven insights.
Responsibilities
- Build robust forecasting models across streaming, audience growth, and commercial performance. Support comprehensive forecasting efforts across deal risk, merchandise, and demand planning.
- Gather and analyze audience data to establish best practices for capturing music listening preferences. Detect anomalies and surface actionable insights from large-scale streaming and engagement data.
- Transform complex data into compelling stories via tailor-made presentations. Develop new hypothesis testing frameworks and decision-making tools for the real-time assessment of audience viewing patterns and music delivery streams.
- Partner with local affiliates, labels, international teams, and Global Technology. Collaborate closely with merchandising teams and business stakeholders to deliver critical reporting and inference.
- Interact directly with data engineering teams to identify, define, and secure the data needs required for mathematical models.
Requirements
- Master's degree (or foreign equivalent) in Statistics, Economics, Mathematics, or a highly related quantitative field.
- 2 to 6 years of professional experience in data science, analytics, or a related field (leveling will be calibrated based on tenure and technical depth).
- 2 to 6 years of hands-on experience working with R, Python, and SQL.
- At least 2 years of experience building forecasting models across streaming, audience growth, and commercial performance, including evaluating forecast accuracy and continuously improving performance through testing, backtesting, and iteration.
- At least 2 years of experience using advertising data to build marketing mix models (measuring the incremental impact of ads/campaigns using techniques like multi-linear regression and Hierarchical Bayes).
- At least 2 years of experience building targeting models, including propensity scoring and look-alike modeling, to develop actionable insights into audience behavior.
- At least 2 years of experience successfully deploying machine learning models into a production environment.
- Proven ability to bridge the gap between technical complexity and business logic, serving as a strategic partner who empowers non-technical teams and leadership to make data-driven decisions.
- At least 2 years of experience communicating complex technical concepts to non-technical stakeholders using data visualizations (e.g., matplotlib, ggplot2, or similar libraries).
Benefits
- performance based annual bonus
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