Our mission on the Advertising Product & Technology team is to build a next generation advertising platform that aligns with our unique value proposition for audio and video. We work to scale the user experience for hundreds of millions of fans and hundreds of thousands of advertisers. This scale brings unique challenges as well as tremendous opportunities for our artists and creators.
We’re looking for a Data Scientist to join
Spotify Advertising’s Growth pod—a team of data scientists and analytics engineers focused on unlocking insights and building scalable data products that power advertisers and revenue growth. Our work spans lead scoring, attribution modeling, metric design, experimentation, and causal inference. As we increase investment in paid media and continue scaling automated buying channels, we’re entering our next phase of growth. While we’ve built strong foundations—including multi-touch attribution (MTA), lifetime value model (LTV) and marketing mix modeling (MMM) — there's a significant opportunity to deepen our insights, refine our models, and drive greater impact.
In this role, you’ll help expand and operationalize our marketing science toolkit—expanding model capabilities and ensuring they inform clear, outcome-driven decisions. Your work may span: Marketing Attribution Models, Paid Media Spend Optimization, Growth Analytics, Forecasting & Scenario Modeling, Incrementality & Lift Measurement, Insights Automation & Dashboards, Data Infrastructure & Signal Engineering. You’ll play a key role in turning complex data into scalable solutions that directly influence how we invest, optimize, and grow.
What You'll Do
- Partner with other data scientists, analytics engineers, and business stakeholders to generate actionable insights that inform paid media strategy and execution
- Contribute to the development and enhancement of marketing attribution models (e.g., MTA, MMM, LTV), working closely with stakeholders to define MMM inputs, establish modeling constraints, validate findings, generate marginal ROAS curves, and translate insights into actionable budget scenario planning.
- Design and implement experiments and statistical models to evaluate incrementality, lift, and media effectiveness, including delivering high-profile experimentation readouts to senior stakeholders.
- Build and maintain data pipelines and dashboards that enable data-informed financial decisions and optimize ROAS and customer LTV
- Translate ambiguous business problems into structured analytical approaches and deliver high-impact solutions independently
- Write production-quality code (Python, SQL, etc.) to manipulate and analyze large-scale datasets
- Communicate clear, data-driven recommendations to both technical and non-technical partners
Who You Are
- 4+ years of experience in a data science role, with a degree in economics, statistics, or a related quantitative field.
- Deep understanding of paid media and digital advertising ecosystems, with hands-on experience in marketing analytics.
- Proven experience building and evolving Marketing Mix Models (MMM), translating model outputs into marginal ROAS curves, budget allocation recommendations, and scenario planning guidance.
- Experience developing and applying multi-touch attribution (MTA) methodologies to inform channel and campaign performance optimization.
- Strong track record designing and analyzing A/B tests and incrementality experiments to measure lift and causal impact.
- Strong foundation in statistics and machine learning, with the technical depth to perform advanced analytics and build robust models.
- Experience building and maintaining data pipelines (e.g., DBT) and developing scalable dashboards in tools such as Tableau and/or Looker to enable self-serve insights.
- Proven ability to solve ambiguous, loosely defined problems and translate them into structured, data-driven solutions.
- Ability to operate independently with minimal oversight while delivering high-quality, reliable work.
- Skilled at building relationships, leading strategic data-driven discussions, and identifying opportunities to support business growth.
- Clear communicator who can translate complex technical concepts into simple, actionable insights to non-technical audiences.
- Motivated to work alongside AI tools, with foundational LLM knowledge and awareness of emerging concepts (e.g., MCP, agent-based systems) and their productivity implications.
Where You'll Be
- We offer you the flexibility to work where you work best! For this role, it can be within the North America region in which we have a work location.
- This team collaborates across the Eastern time zone
The United States base range for this position is $116,995.00 - $167,135.00, plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays. This range encompasses multiple levels. Leveling is determined during the interview process. Placement in a level depends on relevant work history and interview performance. These ranges may be modified in the future.
Spotify is an equal opportunity employer. You are welcome at
Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
At
Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.
Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service.
Originally posted on Himalayas