Data Scientist

Job description

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 turn dreams into stardom and audiences into fans. We are guided by three core values that underpin everything we do across all our diverse businesses: • **Curiosity**: We do our best work when we’re immersing ourselves in culture and breaking through barriers. Curiosity is the driving force behind creativity and ingenuity. It fuels innovation, and innovation is the key to our future. • **Collaboration**: Making music and bringing it to the world is all about the power of originality amplified by teamwork. A great idea, like a great song, travels globally. We ignite passions and build connections across our diverse community of artists, songwriters, partners, and fans. • **Commitment**: We pursue excellence for our team and our talent. Everything in music starts with a leap into the unknown, and we’re committed to keeping the faith, acting with integrity, and delivering on our promises. Technology is one of the most important parts of our business. Whether it’s signing up new artists; ensuring we provide the right data to Spotify, YouTube, and other digital service providers; or helping artists use the latest AI tools and make thoughtful decisions with data-driven insights – technology plays an invaluable role in our success. The engineering team at Warner Music Group makes all of it a reality. Check out first-hand accounts from the WMG engineering, product, design, infrastructure and data teams in [our blog](https://tech.wmg.com/)! WMG is home to a wide range of artists, musicians, and songwriters that fuel our success. That is why we are committed to creating a work environment that actively values, appreciates, and respects everyone. We encourage applications from people with a wide variety of backgrounds and experiences. 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. **The Role** Music is driven by fans, and our data tells their story. We’re looking for a passionate **Data Scientist** to dive into the massive cultural waves happening across major streaming platforms. In this role you’ll be translating billions of signals into the heartbeat of our listeners. Using advanced statistical methods and machine learning, you’ll uncover hidden listener behaviors, build predictive models for artist and commercial performance, and forecast what fans want next. You’ll also measure and optimize the impact of our global marketing campaigns, using experimentation and data driven insights to understand what truly drives engagement. If you’re excited to turn complex data into cultural insight and real world impact, this is the place for you. ### What You'll Do - **Advanced Forecasting & Modeling:** Build robust forecasting models across streaming, audience growth, and commercial performance. Support comprehensive forecasting efforts across deal risk, merchandise, and demand planning. - **Audience Insights & Analytics:** 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. - **Hypothesis Testing & Storytelling:** 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. - **Cross-Functional Collaboration:** Partner with local affiliates, labels, international teams, and Global Technology. You will also collaborate closely with our merchandising teams and business stakeholders to deliver critical reporting and inference. - **Data Engineering Integration:** Interact directly with data engineering teams to identify, define, and secure the data needs required for your mathematical models. ### Who You Are - **Education:** Master's degree (or foreign equivalent) in Statistics, Economics, Mathematics, or a highly related quantitative field. - **Experience:** 5+ years of hands-on DS experience post-BS, or 3+ years of post-Graduate Degree hands-on DS experience - **Technical Stack:** 5+ years of hands-on experience working with R, Python, and SQL. - **Forecasting:** At least 5 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. - **Marketing & Audience Models:** At least 5 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). - **Targeting & Behavior:** At least 5 years of experience building targeting models, including propensity scoring and look-alike modeling, to develop actionable insights into audience behavior. - **Production ML:** At least 5 years of experience successfully deploying machine learning models into a production environment. - **Stakeholder Collaboration:** 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. - **Data Visualization:** At least 5 years of experience communicating complex technical concepts to non-technical stakeholders using data visualizations (e.g., matplotlib, ggplot2, or similar libraries).